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Sample records for biomedical information extraction

  1. Construction of an annotated corpus to support biomedical information extraction

    Directory of Open Access Journals (Sweden)

    McNaught John

    2009-10-01

    Full Text Available Abstract Background Information Extraction (IE is a component of text mining that facilitates knowledge discovery by automatically locating instances of interesting biomedical events from huge document collections. As events are usually centred on verbs and nominalised verbs, understanding the syntactic and semantic behaviour of these words is highly important. Corpora annotated with information concerning this behaviour can constitute a valuable resource in the training of IE components and resources. Results We have defined a new scheme for annotating sentence-bound gene regulation events, centred on both verbs and nominalised verbs. For each event instance, all participants (arguments in the same sentence are identified and assigned a semantic role from a rich set of 13 roles tailored to biomedical research articles, together with a biological concept type linked to the Gene Regulation Ontology. To our knowledge, our scheme is unique within the biomedical field in terms of the range of event arguments identified. Using the scheme, we have created the Gene Regulation Event Corpus (GREC, consisting of 240 MEDLINE abstracts, in which events relating to gene regulation and expression have been annotated by biologists. A novel method of evaluating various different facets of the annotation task showed that average inter-annotator agreement rates fall within the range of 66% - 90%. Conclusion The GREC is a unique resource within the biomedical field, in that it annotates not only core relationships between entities, but also a range of other important details about these relationships, e.g., location, temporal, manner and environmental conditions. As such, it is specifically designed to support bio-specific tool and resource development. It has already been used to acquire semantic frames for inclusion within the BioLexicon (a lexical, terminological resource to aid biomedical text mining. Initial experiments have also shown that the corpus may

  2. BioDARA: Data Summarization Approach to Extracting Bio-Medical Structuring Information

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    Chung S. Kheau

    2011-01-01

    Full Text Available Problem statement: Due to the ever growing amount of biomedical datasets stored in multiple tables, Information Extraction (IE from these datasets is increasingly recognized as one of the crucial technologies in bioinformatics. However, for IE to be practically applicable, adaptability of a system is crucial, considering extremely diverse demands in biomedical IE application. One should be able to extract a set of hidden patterns from these biomedical datasets at low cost. Approach: In this study, a new method is proposed, called Bio-medical Data Aggregation for Relational Attributes (BioDARA, for automatic structuring information extraction for biomedical datasets. BioDARA summarizes biomedical data stored in multiple tables in order to facilitate data modeling efforts in a multi-relational setting. BioDARA has the advantages or capabilities to transform biomedical data stored in multiple tables or databases into a Vector Space model, summarize biomedical data using the Information Retrieval theory and finally extract frequent patterns that describe the characteristics of these biomedical datasets. Results: the results show that data summarization performed by DARA, can be beneficial in summarizing biomedical datasets in a complex multi-relational environment, in which biomedical datasets are stored in a multi-level of one-to-many relationships and also in the case of datasets stored in more than one one-to-many relationships with non-target tables. Conclusion: This study concludes that data summarization performed by BioDARA, can be beneficial in summarizing biomedical datasets in a complex multi-relational environment, in which biomedical datasets are stored in a multi-level of one-to-many relationships.

  3. Non-linear correlation of content and metadata information extracted from biomedical article datasets.

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    Theodosiou, Theodosios; Angelis, Lefteris; Vakali, Athena

    2008-02-01

    Biomedical literature databases constitute valuable repositories of up to date scientific knowledge. The development of efficient machine learning methods in order to facilitate the organization of these databases and the extraction of novel biomedical knowledge is becoming increasingly important. Several of these methods require the representation of the documents as vectors of variables forming large multivariate datasets. Since the amount of information contained in different datasets is voluminous, an open issue is to combine information gained from various sources to a concise new dataset, which will efficiently represent the corpus of documents. This paper investigates the use of the multivariate statistical approach, called Non-Linear Canonical Correlation Analysis (NLCCA), for exploiting the correlation among the variables of different document representations and describing the documents with only one new dataset. Experiments with document datasets represented by text words, Medical Subject Headings (MeSH) and Gene Ontology (GO) terms showed the effectiveness of NLCCA.

  4. Integrating semantic information into multiple kernels for protein-protein interaction extraction from biomedical literatures.

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    Lishuang Li

    Full Text Available Protein-Protein Interaction (PPI extraction is an important task in the biomedical information extraction. Presently, many machine learning methods for PPI extraction have achieved promising results. However, the performance is still not satisfactory. One reason is that the semantic resources were basically ignored. In this paper, we propose a multiple-kernel learning-based approach to extract PPIs, combining the feature-based kernel, tree kernel and semantic kernel. Particularly, we extend the shortest path-enclosed tree kernel (SPT by a dynamic extended strategy to retrieve the richer syntactic information. Our semantic kernel calculates the protein-protein pair similarity and the context similarity based on two semantic resources: WordNet and Medical Subject Heading (MeSH. We evaluate our method with Support Vector Machine (SVM and achieve an F-score of 69.40% and an AUC of 92.00%, which show that our method outperforms most of the state-of-the-art systems by integrating semantic information.

  5. An Effective Approach to Biomedical Information Extraction with Limited Training Data

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    Jonnalagadda, Siddhartha

    2011-01-01

    In the current millennium, extensive use of computers and the internet caused an exponential increase in information. Few research areas are as important as information extraction, which primarily involves extracting concepts and the relations between them from free text. Limitations in the size of training data, lack of lexicons and lack of…

  6. An Effective Approach to Biomedical Information Extraction with Limited Training Data

    CERN Document Server

    Jonnalagadda, Siddhartha

    2011-01-01

    Overall, the two main contributions of this work include the application of sentence simplification to association extraction as described above, and the use of distributional semantics for concept extraction. The proposed work on concept extraction amalgamates for the first time two diverse research areas -distributional semantics and information extraction. This approach renders all the advantages offered in other semi-supervised machine learning systems, and, unlike other proposed semi-supervised approaches, it can be used on top of different basic frameworks and algorithms. http://gradworks.umi.com/34/49/3449837.html

  7. BioSimplify: an open source sentence simplification engine to improve recall in automatic biomedical information extraction

    CERN Document Server

    Jonnalagadda, Siddhartha

    2011-01-01

    BioSimplify is an open source tool written in Java that introduces and facilitates the use of a novel model for sentence simplification tuned for automatic discourse analysis and information extraction (as opposed to sentence simplification for improving human readability). The model is based on a "shot-gun" approach that produces many different (simpler) versions of the original sentence by combining variants of its constituent elements. This tool is optimized for processing biomedical scientific literature such as the abstracts indexed in PubMed. We tested our tool on its impact to the task of PPI extraction and it improved the f-score of the PPI tool by around 7%, with an improvement in recall of around 20%. The BioSimplify tool and test corpus can be downloaded from https://biosimplify.sourceforge.net.

  8. Towards Evidence-based Precision Medicine: Extracting Population Information from Biomedical Text using Binary Classifiers and Syntactic Patterns

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    Raja, Kalpana; Dasot, Naman; Goyal, Pawan; Jonnalagadda, Siddhartha R

    2016-01-01

    Precision Medicine is an emerging approach for prevention and treatment of disease that considers individual variability in genes, environment, and lifestyle for each person. The dissemination of individualized evidence by automatically identifying population information in literature is a key for evidence-based precision medicine at the point-of-care. We propose a hybrid approach using natural language processing techniques to automatically extract the population information from biomedical literature. Our approach first implements a binary classifier to classify sentences with or without population information. A rule-based system based on syntactic-tree regular expressions is then applied to sentences containing population information to extract the population named entities. The proposed two-stage approach achieved an F-score of 0.81 using a MaxEnt classifier and the rule- based system, and an F-score of 0.87 using a Nai've-Bayes classifier and the rule-based system, and performed relatively well compared to many existing systems. The system and evaluation dataset is being released as open source. PMID:27570671

  9. BIMS: Biomedical Information Management System

    OpenAIRE

    Mora, Oscar; Bisbal, Jesús

    2013-01-01

    In this paper, we present BIMS (Biomedical Information Management System). BIMS is a software architecture designed to provide a flexible computational framework to manage the information needs of a wide range of biomedical research projects. The main goal is to facilitate the clinicians' job in data entry, and researcher's tasks in data management, in high data quality biomedical research projects. The BIMS architecture has been designed following the two-level modeling paradigm, a promising...

  10. Parts-of-Speech Tagger Errors Do Not Necessarily Degrade Accuracy in Extracting Information from Biomedical Text

    CERN Document Server

    Ling, Maurice HT; Nicholas, Kevin R

    2008-01-01

    A recent study reported development of Muscorian, a generic text processing tool for extracting protein-protein interactions from text that achieved comparable performance to biomedical-specific text processing tools. This result was unexpected since potential errors from a series of text analysis processes is likely to adversely affect the outcome of the entire process. Most biomedical entity relationship extraction tools have used biomedical-specific parts-of-speech (POS) tagger as errors in POS tagging and are likely to affect subsequent semantic analysis of the text, such as shallow parsing. This study aims to evaluate the parts-of-speech (POS) tagging accuracy and attempts to explore whether a comparable performance is obtained when a generic POS tagger, MontyTagger, was used in place of MedPost, a tagger trained in biomedical text. Our results demonstrated that MontyTagger, Muscorian's POS tagger, has a POS tagging accuracy of 83.1% when tested on biomedical text. Replacing MontyTagger with MedPost did ...

  11. Information extraction

    NARCIS (Netherlands)

    Zhang, Lei; Hoede, C.

    2002-01-01

    In this paper we present a new approach to extract relevant information by knowledge graphs from natural language text. We give a multiple level model based on knowledge graphs for describing template information, and investigate the concept of partial structural parsing. Moreover, we point out that

  12. Biomedical information retrieval across languages.

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    Daumke, Philipp; Markü, Kornél; Poprat, Michael; Schulz, Stefan; Klar, Rüdiger

    2007-06-01

    This work presents a new dictionary-based approach to biomedical cross-language information retrieval (CLIR) that addresses many of the general and domain-specific challenges in current CLIR research. Our method is based on a multilingual lexicon that was generated partly manually and partly automatically, and currently covers six European languages. It contains morphologically meaningful word fragments, termed subwords. Using subwords instead of entire words significantly reduces the number of lexical entries necessary to sufficiently cover a specific language and domain. Mediation between queries and documents is based on these subwords as well as on lists of word-n-grams that are generated from large monolingual corpora and constitute possible translation units. The translations are then sent to a standard Internet search engine. This process makes our approach an effective tool for searching the biomedical content of the World Wide Web in different languages. We evaluate this approach using the OHSUMED corpus, a large medical document collection, within a cross-language retrieval setting.

  13. Mining biomedical images towards valuable information retrieval in biomedical and life sciences.

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    Ahmed, Zeeshan; Zeeshan, Saman; Dandekar, Thomas

    2016-01-01

    Biomedical images are helpful sources for the scientists and practitioners in drawing significant hypotheses, exemplifying approaches and describing experimental results in published biomedical literature. In last decades, there has been an enormous increase in the amount of heterogeneous biomedical image production and publication, which results in a need for bioimaging platforms for feature extraction and analysis of text and content in biomedical images to take advantage in implementing effective information retrieval systems. In this review, we summarize technologies related to data mining of figures. We describe and compare the potential of different approaches in terms of their developmental aspects, used methodologies, produced results, achieved accuracies and limitations. Our comparative conclusions include current challenges for bioimaging software with selective image mining, embedded text extraction and processing of complex natural language queries.

  14. Enhancing biomedical text summarization using semantic relation extraction.

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    Yue Shang

    Full Text Available Automatic text summarization for a biomedical concept can help researchers to get the key points of a certain topic from large amount of biomedical literature efficiently. In this paper, we present a method for generating text summary for a given biomedical concept, e.g., H1N1 disease, from multiple documents based on semantic relation extraction. Our approach includes three stages: 1 We extract semantic relations in each sentence using the semantic knowledge representation tool SemRep. 2 We develop a relation-level retrieval method to select the relations most relevant to each query concept and visualize them in a graphic representation. 3 For relations in the relevant set, we extract informative sentences that can interpret them from the document collection to generate text summary using an information retrieval based method. Our major focus in this work is to investigate the contribution of semantic relation extraction to the task of biomedical text summarization. The experimental results on summarization for a set of diseases show that the introduction of semantic knowledge improves the performance and our results are better than the MEAD system, a well-known tool for text summarization.

  15. A Unified Active Learning Framework for Biomedical Relation Extraction

    Institute of Scientific and Technical Information of China (English)

    Hong-Tao Zhang; Min-Lie Huang; Xiao-Yan Zhu

    2012-01-01

    Supervised machine learning methods have been employed with great success in the task of biomedical relation extraction.However,existing methods are not practical enough,since manual construction of large training data is very expensive.Therefore,active learning is urgently needed for designing practical relation extraction methods with little human effort.In this paper,we describe a unified active learning framework.Particularly,our framework systematically addresses some practical issues during active learning process,including a strategy for selecting informative data,a data diversity selection algorithm,an active feature acquisition method,and an informative feature selection algorithm,in order to meet the challenges due to the immense amount of complex and diverse biomedical text.The framework is evaluated on protein-protein interaction (PPI) extraction and is shown to achieve promising results with a significant reduction in editorial effort and labeling time.

  16. Cross language information retrieval for biomedical literature

    NARCIS (Netherlands)

    Schuemie, M.; Trieschnigg, D.; Kraaij, W.

    2007-01-01

    This workshop report discusses the collaborative work of UT, EMC and TNO on the TREC Genomics Track 2007. The biomedical information retrieval task is approached using cross language methods, in which biomedical concept detection is combined with effective IR based on unigram language models. Furthe

  17. Document Exploration and Automatic Knowledge Extraction for Unstructured Biomedical Text

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    Chu, S.; Totaro, G.; Doshi, N.; Thapar, S.; Mattmann, C. A.; Ramirez, P.

    2015-12-01

    We describe our work on building a web-browser based document reader with built-in exploration tool and automatic concept extraction of medical entities for biomedical text. Vast amounts of biomedical information are offered in unstructured text form through scientific publications and R&D reports. Utilizing text mining can help us to mine information and extract relevant knowledge from a plethora of biomedical text. The ability to employ such technologies to aid researchers in coping with information overload is greatly desirable. In recent years, there has been an increased interest in automatic biomedical concept extraction [1, 2] and intelligent PDF reader tools with the ability to search on content and find related articles [3]. Such reader tools are typically desktop applications and are limited to specific platforms. Our goal is to provide researchers with a simple tool to aid them in finding, reading, and exploring documents. Thus, we propose a web-based document explorer, which we called Shangri-Docs, which combines a document reader with automatic concept extraction and highlighting of relevant terms. Shangri-Docsalso provides the ability to evaluate a wide variety of document formats (e.g. PDF, Words, PPT, text, etc.) and to exploit the linked nature of the Web and personal content by performing searches on content from public sites (e.g. Wikipedia, PubMed) and private cataloged databases simultaneously. Shangri-Docsutilizes Apache cTAKES (clinical Text Analysis and Knowledge Extraction System) [4] and Unified Medical Language System (UMLS) to automatically identify and highlight terms and concepts, such as specific symptoms, diseases, drugs, and anatomical sites, mentioned in the text. cTAKES was originally designed specially to extract information from clinical medical records. Our investigation leads us to extend the automatic knowledge extraction process of cTAKES for biomedical research domain by improving the ontology guided information extraction

  18. A robust approach to extract biomedical events from literature

    NARCIS (Netherlands)

    Bui, Q.C.; Sloot, P.M.A.

    2012-01-01

    Motivation: The abundance of biomedical literature has attracted significant interest in novel methods to automatically extract biomedical relations from the literature. Until recently, most research was focused on extracting binary relations such as protein-protein interactions and drug-disease rel

  19. A Relation Extraction Framework for Biomedical Text Using Hybrid Feature Set.

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    Muzaffar, Abdul Wahab; Azam, Farooque; Qamar, Usman

    2015-01-01

    The information extraction from unstructured text segments is a complex task. Although manual information extraction often produces the best results, it is harder to manage biomedical data extraction manually because of the exponential increase in data size. Thus, there is a need for automatic tools and techniques for information extraction in biomedical text mining. Relation extraction is a significant area under biomedical information extraction that has gained much importance in the last two decades. A lot of work has been done on biomedical relation extraction focusing on rule-based and machine learning techniques. In the last decade, the focus has changed to hybrid approaches showing better results. This research presents a hybrid feature set for classification of relations between biomedical entities. The main contribution of this research is done in the semantic feature set where verb phrases are ranked using Unified Medical Language System (UMLS) and a ranking algorithm. Support Vector Machine and Naïve Bayes, the two effective machine learning techniques, are used to classify these relations. Our approach has been validated on the standard biomedical text corpus obtained from MEDLINE 2001. Conclusively, it can be articulated that our framework outperforms all state-of-the-art approaches used for relation extraction on the same corpus.

  20. A Relation Extraction Framework for Biomedical Text Using Hybrid Feature Set

    Directory of Open Access Journals (Sweden)

    Abdul Wahab Muzaffar

    2015-01-01

    Full Text Available The information extraction from unstructured text segments is a complex task. Although manual information extraction often produces the best results, it is harder to manage biomedical data extraction manually because of the exponential increase in data size. Thus, there is a need for automatic tools and techniques for information extraction in biomedical text mining. Relation extraction is a significant area under biomedical information extraction that has gained much importance in the last two decades. A lot of work has been done on biomedical relation extraction focusing on rule-based and machine learning techniques. In the last decade, the focus has changed to hybrid approaches showing better results. This research presents a hybrid feature set for classification of relations between biomedical entities. The main contribution of this research is done in the semantic feature set where verb phrases are ranked using Unified Medical Language System (UMLS and a ranking algorithm. Support Vector Machine and Naïve Bayes, the two effective machine learning techniques, are used to classify these relations. Our approach has been validated on the standard biomedical text corpus obtained from MEDLINE 2001. Conclusively, it can be articulated that our framework outperforms all state-of-the-art approaches used for relation extraction on the same corpus.

  1. [The need for information in biomedical research].

    Science.gov (United States)

    Kumate, J

    1981-01-01

    This paper focuses on the need of every researcher to be informed on advances in his field. It reviews the means available for keeping abreast of developments in a specific area of scientific inquiry. In the author's view, articles in reference journals on a specific specialty are the best source of information. However, the interval between the writing and publication of a scientific paper is sometimes long, which poses a considerable impediment to the use of the traditional media as a means of keeping up. He also examines the limitations of information in biomedical research and reviews the characteristics of this research in Latin America. Finally, he makes a number of recommendations for improving scientific communications and making the most of the services of national and international information dissemination systems.

  2. A concept-driven biomedical knowledge extraction and visualization framework for conceptualization of text corpora.

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    Jahiruddin; Abulaish, Muhammad; Dey, Lipika

    2010-12-01

    A number of techniques such as information extraction, document classification, document clustering and information visualization have been developed to ease extraction and understanding of information embedded within text documents. However, knowledge that is embedded in natural language texts is difficult to extract using simple pattern matching techniques and most of these methods do not help users directly understand key concepts and their semantic relationships in document corpora, which are critical for capturing their conceptual structures. The problem arises due to the fact that most of the information is embedded within unstructured or semi-structured texts that computers can not interpret very easily. In this paper, we have presented a novel Biomedical Knowledge Extraction and Visualization framework, BioKEVis to identify key information components from biomedical text documents. The information components are centered on key concepts. BioKEVis applies linguistic analysis and Latent Semantic Analysis (LSA) to identify key concepts. The information component extraction principle is based on natural language processing techniques and semantic-based analysis. The system is also integrated with a biomedical named entity recognizer, ABNER, to tag genes, proteins and other entity names in the text. We have also presented a method for collating information extracted from multiple sources to generate semantic network. The network provides distinct user perspectives and allows navigation over documents with similar information components and is also used to provide a comprehensive view of the collection. The system stores the extracted information components in a structured repository which is integrated with a query-processing module to handle biomedical queries over text documents. We have also proposed a document ranking mechanism to present retrieved documents in order of their relevance to the user query.

  3. Information extraction system

    Science.gov (United States)

    Lemmond, Tracy D; Hanley, William G; Guensche, Joseph Wendell; Perry, Nathan C; Nitao, John J; Kidwell, Paul Brandon; Boakye, Kofi Agyeman; Glaser, Ron E; Prenger, Ryan James

    2014-05-13

    An information extraction system and methods of operating the system are provided. In particular, an information extraction system for performing meta-extraction of named entities of people, organizations, and locations as well as relationships and events from text documents are described herein.

  4. Electromembrane extraction for pharmaceutical and biomedical analysis

    DEFF Research Database (Denmark)

    Huang, Chuixiu; Seip, Knut Fredrik; Gjelstad, Astrid

    2015-01-01

    Electromembrane extraction (EME) was presented as a new microextraction concept in 2006, and since the introduction, substantial research has been conducted to develop this concept in different areas of analytical chemistry. To date, more than 100 research papers have been published on EME...

  5. An efficient semi-blind source extraction algorithm and its applications to biomedical signal extraction

    Institute of Scientific and Technical Information of China (English)

    YE YaLan; SHEU Phillip C-Y; ZENG JiaZhi; WANG Gang; LU Ke

    2009-01-01

    In many applications, such as biomedical engineering, it is often required to extract a desired signal instead of all source signals. This can be achieved by blind source extraction (BSE) or semi-blind source extraction, which is a powerful technique emerging from the neural network field. In this paper, we propose an efficient semi-blind source extraction algorithm to extract a desired source signal as its first output signal by using a priori information about its kurtosis range. The algorithm is robust to outliers and spiky noise because of adopting a classical robust contrast function. And it is also robust to the estimation errors of the kurtoaia range of the desired signal providing the estimation errors are not large. The algorithm has good extraction performance, even in some poor situations when the kurtosis values of some source signals are very close to each other. Its convergence stability and robustness are theoretically analyzed. Simulations and experiments on artificial generated data and real-world data have confirmed these results.

  6. MBA: a literature mining system for extracting biomedical abbreviations

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    Lei YiMing

    2009-01-01

    Full Text Available Abstract Background The exploding growth of the biomedical literature presents many challenges for biological researchers. One such challenge is from the use of a great deal of abbreviations. Extracting abbreviations and their definitions accurately is very helpful to biologists and also facilitates biomedical text analysis. Existing approaches fall into four broad categories: rule based, machine learning based, text alignment based and statistically based. State of the art methods either focus exclusively on acronym-type abbreviations, or could not recognize rare abbreviations. We propose a systematic method to extract abbreviations effectively. At first a scoring method is used to classify the abbreviations into acronym-type and non-acronym-type abbreviations, and then their corresponding definitions are identified by two different methods: text alignment algorithm for the former, statistical method for the latter. Results A literature mining system MBA was constructed to extract both acronym-type and non-acronym-type abbreviations. An abbreviation-tagged literature corpus, called Medstract gold standard corpus, was used to evaluate the system. MBA achieved a recall of 88% at the precision of 91% on the Medstract gold-standard EVALUATION Corpus. Conclusion We present a new literature mining system MBA for extracting biomedical abbreviations. Our evaluation demonstrates that the MBA system performs better than the others. It can identify the definition of not only acronym-type abbreviations including a little irregular acronym-type abbreviations (e.g., , but also non-acronym-type abbreviations (e.g., .

  7. A cross-lingual framework for monolingual biomedical information retrieval

    NARCIS (Netherlands)

    Trieschnigg, D.; Hiemstra, D.; Jong, F. de; Kraaij, W.

    2010-01-01

    An important challenge for biomedical information retrieval (IR) is dealing with the complex, inconsistent and ambiguous biomedical terminology. Frequently, a concept-based representation defined in terms of a domain-specific terminological resource is employed to deal with this challenge. In this p

  8. DeTEXT: A Database for Evaluating Text Extraction from Biomedical Literature Figures.

    Science.gov (United States)

    Yin, Xu-Cheng; Yang, Chun; Pei, Wei-Yi; Man, Haixia; Zhang, Jun; Learned-Miller, Erik; Yu, Hong

    2015-01-01

    Hundreds of millions of figures are available in biomedical literature, representing important biomedical experimental evidence. Since text is a rich source of information in figures, automatically extracting such text may assist in the task of mining figure information. A high-quality ground truth standard can greatly facilitate the development of an automated system. This article describes DeTEXT: A database for evaluating text extraction from biomedical literature figures. It is the first publicly available, human-annotated, high quality, and large-scale figure-text dataset with 288 full-text articles, 500 biomedical figures, and 9308 text regions. This article describes how figures were selected from open-access full-text biomedical articles and how annotation guidelines and annotation tools were developed. We also discuss the inter-annotator agreement and the reliability of the annotations. We summarize the statistics of the DeTEXT data and make available evaluation protocols for DeTEXT. Finally we lay out challenges we observed in the automated detection and recognition of figure text and discuss research directions in this area. DeTEXT is publicly available for downloading at http://prir.ustb.edu.cn/DeTEXT/.

  9. Utilization of ontology look-up services in information retrieval for biomedical literature.

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    Vishnyakova, Dina; Pasche, Emilie; Lovis, Christian; Ruch, Patrick

    2013-01-01

    With the vast amount of biomedical data we face the necessity to improve information retrieval processes in biomedical domain. The use of biomedical ontologies facilitated the combination of various data sources (e.g. scientific literature, clinical data repository) by increasing the quality of information retrieval and reducing the maintenance efforts. In this context, we developed Ontology Look-up services (OLS), based on NEWT and MeSH vocabularies. Our services were involved in some information retrieval tasks such as gene/disease normalization. The implementation of OLS services significantly accelerated the extraction of particular biomedical facts by structuring and enriching the data context. The results of precision in normalization tasks were boosted on about 20%.

  10. An unsupervised text mining method for relation extraction from biomedical literature.

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    Quan, Changqin; Wang, Meng; Ren, Fuji

    2014-01-01

    The wealth of interaction information provided in biomedical articles motivated the implementation of text mining approaches to automatically extract biomedical relations. This paper presents an unsupervised method based on pattern clustering and sentence parsing to deal with biomedical relation extraction. Pattern clustering algorithm is based on Polynomial Kernel method, which identifies interaction words from unlabeled data; these interaction words are then used in relation extraction between entity pairs. Dependency parsing and phrase structure parsing are combined for relation extraction. Based on the semi-supervised KNN algorithm, we extend the proposed unsupervised approach to a semi-supervised approach by combining pattern clustering, dependency parsing and phrase structure parsing rules. We evaluated the approaches on two different tasks: (1) Protein-protein interactions extraction, and (2) Gene-suicide association extraction. The evaluation of task (1) on the benchmark dataset (AImed corpus) showed that our proposed unsupervised approach outperformed three supervised methods. The three supervised methods are rule based, SVM based, and Kernel based separately. The proposed semi-supervised approach is superior to the existing semi-supervised methods. The evaluation on gene-suicide association extraction on a smaller dataset from Genetic Association Database and a larger dataset from publicly available PubMed showed that the proposed unsupervised and semi-supervised methods achieved much higher F-scores than co-occurrence based method.

  11. An unsupervised text mining method for relation extraction from biomedical literature.

    Directory of Open Access Journals (Sweden)

    Changqin Quan

    Full Text Available The wealth of interaction information provided in biomedical articles motivated the implementation of text mining approaches to automatically extract biomedical relations. This paper presents an unsupervised method based on pattern clustering and sentence parsing to deal with biomedical relation extraction. Pattern clustering algorithm is based on Polynomial Kernel method, which identifies interaction words from unlabeled data; these interaction words are then used in relation extraction between entity pairs. Dependency parsing and phrase structure parsing are combined for relation extraction. Based on the semi-supervised KNN algorithm, we extend the proposed unsupervised approach to a semi-supervised approach by combining pattern clustering, dependency parsing and phrase structure parsing rules. We evaluated the approaches on two different tasks: (1 Protein-protein interactions extraction, and (2 Gene-suicide association extraction. The evaluation of task (1 on the benchmark dataset (AImed corpus showed that our proposed unsupervised approach outperformed three supervised methods. The three supervised methods are rule based, SVM based, and Kernel based separately. The proposed semi-supervised approach is superior to the existing semi-supervised methods. The evaluation on gene-suicide association extraction on a smaller dataset from Genetic Association Database and a larger dataset from publicly available PubMed showed that the proposed unsupervised and semi-supervised methods achieved much higher F-scores than co-occurrence based method.

  12. Multimedia Information Extraction

    CERN Document Server

    Maybury, Mark T

    2012-01-01

    The advent of increasingly large consumer collections of audio (e.g., iTunes), imagery (e.g., Flickr), and video (e.g., YouTube) is driving a need not only for multimedia retrieval but also information extraction from and across media. Furthermore, industrial and government collections fuel requirements for stock media access, media preservation, broadcast news retrieval, identity management, and video surveillance.  While significant advances have been made in language processing for information extraction from unstructured multilingual text and extraction of objects from imagery and vid

  13. Biomedical and Environmental Sciences INFORMATION FOR AUTHORS

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    @@ Biomedical and Environmental Sciences, an international journal with emphasis on scientific findings in China, publishes articles dealing with biologic and toxic effects of environmental pollutants on man and other forms of life. The effects may be measured with pharmacological, biochemical, pathological, and immunological techniques. The journal also publishes reports dealing with the entry, transport, and fate of natural and anthropogenic chemicals in the biosphere, and their impact on human health and well-being.Papers describing biochemical, pharmacological, pathological, toxicological and immunological studies of pharmaceuticals (biotechnological products) are also welcome.

  14. Use of controlled vocabularies to improve biomedical information retrieval tasks.

    Science.gov (United States)

    Pasche, Emilie; Gobeill, Julien; Vishnyakova, Dina; Ruch, Patrick; Lovis, Christian

    2013-01-01

    The high heterogeneity of biomedical vocabulary is a major obstacle for information retrieval in large biomedical collections. Therefore, using biomedical controlled vocabularies is crucial for managing these contents. We investigate the impact of query expansion based on controlled vocabularies to improve the effectiveness of two search engines. Our strategy relies on the enrichment of users' queries with additional terms, directly derived from such vocabularies applied to infectious diseases and chemical patents. We observed that query expansion based on pathogen names resulted in improvements of the top-precision of our first search engine, while the normalization of diseases degraded the top-precision. The expansion of chemical entities, which was performed on the second search engine, positively affected the mean average precision. We have shown that query expansion of some types of biomedical entities has a great potential to improve search effectiveness; therefore a fine-tuning of query expansion strategies could help improving the performances of search engines.

  15. [The system of biomedical scientific information of Serbia].

    Science.gov (United States)

    Dacić, M

    1995-09-01

    Building of the System of biomedical scientific information of Yugoslavia (SBMSI YU) began, by the end of 1980, and the system became operative officially in 1986. After the political disintegration of former Yugoslavia SBMSI of Serbia was formed. SBMSI is developed according to the policy of developing of the System of scientific technologic information of Serbia (SSTI S), and with technical support of SSTI S. Reconstruction of the System is done by using former SBMSI YU as a model. Unlike the former SBMSI YU, SBMSI S owns besides the database Biomedicina Serbica, three important databases: database of doctoral dissertations promoted at University Medical School in Belgrade in the period from 1955-1993, database of Master's theses promoted at the University School of Medicine in Belgrade from 1965-1993; A database of foreign biomedical periodicals in libraries of Serbia.

  16. Information Retrieval Systems Adapted to the Biomedical Domain

    CERN Document Server

    Marrero, Mónica; Urbano, Julián; Morato, Jorge; Moreiro, José-Antonio; 10.3145/epi.2010.may.04

    2012-01-01

    The terminology used in Biomedicine shows lexical peculiarities that have required the elaboration of terminological resources and information retrieval systems with specific functionalities. The main characteristics are the high rates of synonymy and homonymy, due to phenomena such as the proliferation of polysemic acronyms and their interaction with common language. Information retrieval systems in the biomedical domain use techniques oriented to the treatment of these lexical peculiarities. In this paper we review some of the techniques used in this domain, such as the application of Natural Language Processing (BioNLP), the incorporation of lexical-semantic resources, and the application of Named Entity Recognition (BioNER). Finally, we present the evaluation methods adopted to assess the suitability of these techniques for retrieving biomedical resources.

  17. PIMiner: A web tool for extraction of protein interactions from biomedical literature

    KAUST Repository

    Chowdhary, Rajesh

    2013-01-01

    Information on Protein Interactions (PIs) is valuable for biomedical research, but often lies buried in the scientific literature and cannot be readily retrieved. While much progress has been made over the years in extracting PIs from the literature using computational methods, there is a lack of free, public, user-friendly tools for the discovery of PIs. We developed an online tool for the extraction of PI relationships from PubMed-abstracts, which we name PIMiner. Protein pairs and the words that describe their interactions are reported by PIMiner so that new interactions can be easily detected within text. The interaction likelihood levels are reported too. The option to extract only specific types of interactions is also provided. The PIMiner server can be accessed through a web browser or remotely through a client\\'s command line. PIMiner can process 50,000 PubMed abstracts in approximately 7 min and thus appears suitable for large-scale processing of biological/biomedical literature. Copyright © 2013 Inderscience Enterprises Ltd.

  18. Tree kernel-based protein-protein interaction extraction from biomedical literature.

    Science.gov (United States)

    Qian, Longhua; Zhou, Guodong

    2012-06-01

    There is a surge of research interest in protein-protein interaction (PPI) extraction from biomedical literature. While most of the state-of-the-art PPI extraction systems focus on dependency-based structured information, the rich structured information inherent in constituent parse trees has not been extensively explored for PPI extraction. In this paper, we propose a novel approach to tree kernel-based PPI extraction, where the tree representation generated from a constituent syntactic parser is further refined using the shortest dependency path between two proteins derived from a dependency parser. Specifically, all the constituent tree nodes associated with the nodes on the shortest dependency path are kept intact, while other nodes are removed safely to make the constituent tree concise and precise for PPI extraction. Compared with previously used constituent tree setups, our dependency-motivated constituent tree setup achieves the best results across five commonly used PPI corpora. Moreover, our tree kernel-based method outperforms other single kernel-based ones and performs comparably with some multiple kernel ones on the most commonly tested AIMed corpus.

  19. Information-theoretic evaluation for computational biomedical ontologies

    CERN Document Server

    Clark, Wyatt Travis

    2014-01-01

    The development of effective methods for the prediction of ontological annotations is an important goal in computational biology, yet evaluating their performance is difficult due to problems caused by the structure of biomedical ontologies and incomplete annotations of genes. This work proposes an information-theoretic framework to evaluate the performance of computational protein function prediction. A Bayesian network is used, structured according to the underlying ontology, to model the prior probability of a protein's function. The concepts of misinformation and remaining uncertainty are

  20. Knowledge-based method for determining the meaning of ambiguous biomedical terms using information content measures of similarity.

    Science.gov (United States)

    McInnes, Bridget T; Pedersen, Ted; Liu, Ying; Melton, Genevieve B; Pakhomov, Serguei V

    2011-01-01

    In this paper, we introduce a novel knowledge-based word sense disambiguation method that determines the sense of an ambiguous word in biomedical text using semantic similarity or relatedness measures. These measures quantify the degree of similarity between concepts in the Unified Medical Language System (UMLS). The objective of this work was to develop a method that can disambiguate terms in biomedical text by exploiting similarity information extracted from the UMLS and to evaluate the efficacy of information content-based semantic similarity measures, which augment path-based information with probabilities derived from biomedical corpora. We show that information content-based measures obtain a higher disambiguation accuracy than path-based measures because they weight the path based on where it exists in the taxonomy coupled with the probability of the concepts occurring in a corpus of text.

  1. Utilization of ontology look-up services in information retrieval for biomedical literature

    OpenAIRE

    2014-01-01

    With the vast amount of biomedical data we face the necessity to improve information retrieval processes in biomedical domain. The use of biomedical ontologies facilitated the combination of various data sources (e.g. scientific literature, clinical data repository) by increasing the quality of information retrieval and reducing the maintenance efforts. In this context, we developed Ontology Look-up services (OLS), based on NEWT and MeSH vocabularies. Our services were involved in some inform...

  2. Properties of herbal extracts against Propionibacterium acnes for biomedical application

    Science.gov (United States)

    Lim, Youn-Mook; Kim, Sung Eun; Kim, Yong Soo; Shin, Young Min; Jeong, Sung In; Jo, Sun-Young; Gwon, Hui-Jeong; Park, Jong-seok; Nho, Young-Chang; Kim, Jong-Cheol; Kim, Seong-Jang; Shin, HeungSoo

    2012-10-01

    Propionibacterium acnes (P. acnes), one of the anaerobic bacterium, causes inflammatory acne. To find a novel medication for treating the inflammation caused by P. acnes, we investigated the anti-bacterial and anti-inflammatory activities of several herbal extracts against P. acnes. The aqueous extracts from five dried herbs, Phellodendron amurense Rupr., Paeonia lactiflora Pallas., Houttuynia cordata Thunb., Agrimonia pilosa Ledeb. and Glycyrrhiza uralensis Fisch., were prepared and mixed. In this experiment, 1 mg/ml of the herbal extract mixture caused a decrease in the growth of P. acnes and reduced the production of pro-inflammatory cytokines, TNF-α, IL-8, IL-1β and IL-6, in human monocytic THP-1 cells treated with heat-killed P. acnes. Therefore, this herbal extract mixture may possess both anti-bacterial and anti-inflammatory activities against P. acnes and can be a novel therapeutic agent for treating inflammatory acne.

  3. Extracting useful information from images

    DEFF Research Database (Denmark)

    Kucheryavskiy, Sergey

    2011-01-01

    The paper presents an overview of methods for extracting useful information from digital images. It covers various approaches that utilized different properties of images, like intensity distribution, spatial frequencies content and several others. A few case studies including isotropic...... and heterogeneous, congruent and non-congruent images are used to illustrate how the described methods work and to compare some of them...

  4. Informed consent in dental extractions.

    Directory of Open Access Journals (Sweden)

    José Luis Capote Femenías

    2009-07-01

    Full Text Available When performing any oral intervention, particularly dental extractions, the specialist should have the oral or written consent of the patient. This consent includes the explanation of all possible complications, whether typical, very serious or personalized associated with the previous health condition, age, profession, religion or any other characteristic of the patient, as well as the possi.ble benefits of the intervention. This article is related with the bioethical aspects related with dental extractions, in order to determine the main elements that the informed consent should include.

  5. Extraction of semantic biomedical relations from text using conditional random fields

    Directory of Open Access Journals (Sweden)

    Stetter Martin

    2008-04-01

    Full Text Available Abstract Background The increasing amount of published literature in biomedicine represents an immense source of knowledge, which can only efficiently be accessed by a new generation of automated information extraction tools. Named entity recognition of well-defined objects, such as genes or proteins, has achieved a sufficient level of maturity such that it can form the basis for the next step: the extraction of relations that exist between the recognized entities. Whereas most early work focused on the mere detection of relations, the classification of the type of relation is also of great importance and this is the focus of this work. In this paper we describe an approach that extracts both the existence of a relation and its type. Our work is based on Conditional Random Fields, which have been applied with much success to the task of named entity recognition. Results We benchmark our approach on two different tasks. The first task is the identification of semantic relations between diseases and treatments. The available data set consists of manually annotated PubMed abstracts. The second task is the identification of relations between genes and diseases from a set of concise phrases, so-called GeneRIF (Gene Reference Into Function phrases. In our experimental setting, we do not assume that the entities are given, as is often the case in previous relation extraction work. Rather the extraction of the entities is solved as a subproblem. Compared with other state-of-the-art approaches, we achieve very competitive results on both data sets. To demonstrate the scalability of our solution, we apply our approach to the complete human GeneRIF database. The resulting gene-disease network contains 34758 semantic associations between 4939 genes and 1745 diseases. The gene-disease network is publicly available as a machine-readable RDF graph. Conclusion We extend the framework of Conditional Random Fields towards the annotation of semantic relations from

  6. Extraction and Characterization of Collagen from Buffalo Skin for Biomedical Applications

    OpenAIRE

    Moustafa A. Rizk; Nasser Y. Mostafa

    2016-01-01

    Collagen is widely used for biomedical and pharmaceutical applications due to its excellent biocompatibility, biodegradability and weak antigenicity. However, applicability is limited due to its high cost and probability of disease transmission from the current sources, which are bovine and porcine. In the present study, collagen was extracted from 6 months buffalo skins as alternative save sources. Collagen was characterized by different physico-chemical techniques like ATR-FTIR, Raman, SEM...

  7. A Semantics-Based Approach to Retrieving Biomedical Information

    DEFF Research Database (Denmark)

    Andreasen, Troels; Bulskov, Henrik; Zambach, Sine

    2011-01-01

    This paper describes an approach to representing, organising, and accessing conceptual content of biomedical texts using a formal ontology. The ontology is based on UMLS resources supplemented with domain ontologies developed in the project. The approach introduces the notion of ‘generative...

  8. Web-Based Information Extraction Technology

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    Information extraction techniques on the Web are the current research hotspot. Now many information extraction techniques based on different principles have appeared and have different capabilities. We classify the existing information extraction techniques by the principle of information extraction and analyze the methods and principles of semantic information adding, schema defining,rule expression, semantic items locating and object locating in the approaches. Based on the above survey and analysis,several open problems are discussed.

  9. Using text mining techniques to extract phenotypic information from the PhenoCHF corpus

    OpenAIRE

    Alnazzawi, Noha; Thompson, Paul; Batista-Navarro, Riza; Ananiadou, Sophia

    2015-01-01

    Background Phenotypic information locked away in unstructured narrative text presents significant barriers to information accessibility, both for clinical practitioners and for computerised applications used for clinical research purposes. Text mining (TM) techniques have previously been applied successfully to extract different types of information from text in the biomedical domain. They have the potential to be extended to allow the extraction of information relating to phenotypes from fre...

  10. Information Extraction and Webpage Understanding

    Directory of Open Access Journals (Sweden)

    M.Sharmila Begum

    2011-11-01

    Full Text Available The two most important tasks in information extraction from the Web are webpage structure understanding and natural language sentences processing. However, little work has been done toward an integrated statistical model for understanding webpage structures and processing natural language sentences within the HTML elements. Our recent work on webpage understanding introduces a joint model of Hierarchical Conditional Random Fields (HCRFs and extended Semi-Markov Conditional Random Fields (Semi-CRFs to leverage the page structure understanding results in free text segmentation and labeling. In this top-down integration model, the decision of the HCRF model could guide the decision making of the Semi-CRF model. However, the drawback of the topdown integration strategy is also apparent, i.e., the decision of the Semi-CRF model could not be used by the HCRF model to guide its decision making. This paper proposed a novel framework called WebNLP, which enables bidirectional integration of page structure understanding and text understanding in an iterative manner. We have applied the proposed framework to local business entity extraction and Chinese person and organization name extraction. Experiments show that the WebNLP framework achieved significantly better performance than existing methods.

  11. Down syndrome screening information in midwifery practices in the Netherlands: Strategies to integrate biomedical information.

    Science.gov (United States)

    Rosman, Sophia

    2016-03-01

    The aim of this qualitative study was to analyse counselling with regard to prenatal screening in midwifery consultations in the Netherlands where a national prenatal screening programme has only existed since 2007, after years of social and political debates. The methodology is based on in situ observations of 25 counselling consultations in four midwifery practices in two main cities in the Netherlands. The results of this study show that, since midwives are obliged to offer information on Down syndrome screening to all pregnant women (2007), they have to deal with the communication of medical screening information using biostatistical concepts to explain risks, calculations, probabilities and chromosomal anomalies. In order to avoid the risk of medicalization of their consultation, midwives develop strategies that allow them to integrate this new biomedical discourse while maintaining their low medicalized approach of midwife-led care. One of their main strategies is to switch from 'alarming' biomedical messages to 'reassuring words' in order to manage the anxiety induced by the information and to keep the control over their low medicalized consultation. They also tend to distance themselves from the obligation to talk about screening. The way midwives handle these counselling consultations allows them to respect their obligation to propose information, and to remain faithful to their struggle to protect the natural process of pregnancy as well as their professional autonomy.

  12. A comparison of hypertext and Boolean access to biomedical information.

    Science.gov (United States)

    Friedman, C P; Wildemuth, B M; Muriuki, M; Gant, S P; Downs, S M; Twarog, R G; de Bliek, R

    1996-01-01

    This study explored which of two modes of access to a biomedical database better supported problem solving in bacteriology. Boolean access, which allowed subjects to frame their queries as combinations of keywords, was compared to hypertext access, which allowed subjects to navigate from one database node to another. The accessible biomedical data were identical across systems. Data were collected from 42 first year medical students, each randomized to the Boolean or hypertext system, before and after their bacteriology course. Subjects worked eight clinical case problems, first using only their personal knowledge and, subsequently, with aid from the database. Database retrievals enabled students to answer questions they could not answer based on personal knowledge only. This effect was greater when personal knowledge of bacteriology was lower. The results also suggest that hypertext was superior to Boolean access in helping subjects identify possible infectious agents in these clinical case problems.

  13. Resource Disambiguator for the Web: Extracting Biomedical Resources and Their Citations from the Scientific Literature.

    Science.gov (United States)

    Ozyurt, Ibrahim Burak; Grethe, Jeffrey S; Martone, Maryann E; Bandrowski, Anita E

    2016-01-01

    The NIF Registry developed and maintained by the Neuroscience Information Framework is a cooperative project aimed at cataloging research resources, e.g., software tools, databases and tissue banks, funded largely by governments and available as tools to research scientists. Although originally conceived for neuroscience, the NIF Registry has over the years broadened in the scope to include research resources of general relevance to biomedical research. The current number of research resources listed by the Registry numbers over 13K. The broadening in scope to biomedical science led us to re-christen the NIF Registry platform as SciCrunch. The NIF/SciCrunch Registry has been cataloging the resource landscape since 2006; as such, it serves as a valuable dataset for tracking the breadth, fate and utilization of these resources. Our experience shows research resources like databases are dynamic objects, that can change location and scope over time. Although each record is entered manually and human-curated, the current size of the registry requires tools that can aid in curation efforts to keep content up to date, including when and where such resources are used. To address this challenge, we have developed an open source tool suite, collectively termed RDW: Resource Disambiguator for the (Web). RDW is designed to help in the upkeep and curation of the registry as well as in enhancing the content of the registry by automated extraction of resource candidates from the literature. The RDW toolkit includes a URL extractor from papers, resource candidate screen, resource URL change tracker, resource content change tracker. Curators access these tools via a web based user interface. Several strategies are used to optimize these tools, including supervised and unsupervised learning algorithms as well as statistical text analysis. The complete tool suite is used to enhance and maintain the resource registry as well as track the usage of individual resources through an

  14. Semantic characteristics of NLP-extracted concepts in clinical notes vs. biomedical literature.

    Science.gov (United States)

    Wu, Stephen; Liu, Hongfang

    2011-01-01

    Natural language processing (NLP) has become crucial in unlocking information stored in free text, from both clinical notes and biomedical literature. Clinical notes convey clinical information related to individual patient health care, while biomedical literature communicates scientific findings. This work focuses on semantic characterization of texts at an enterprise scale, comparing and contrasting the two domains and their NLP approaches. We analyzed the empirical distributional characteristics of NLP-discovered named entities in Mayo Clinic clinical notes from 2001-2010, and in the 2011 MetaMapped Medline Baseline. We give qualitative and quantitative measures of domain similarity and point to the feasibility of transferring resources and techniques. An important by-product for this study is the development of a weighted ontology for each domain, which gives distributional semantic information that may be used to improve NLP applications.

  15. Extracting information from multiplex networks.

    Science.gov (United States)

    Iacovacci, Jacopo; Bianconi, Ginestra

    2016-06-01

    Multiplex networks are generalized network structures that are able to describe networks in which the same set of nodes are connected by links that have different connotations. Multiplex networks are ubiquitous since they describe social, financial, engineering, and biological networks as well. Extending our ability to analyze complex networks to multiplex network structures increases greatly the level of information that is possible to extract from big data. For these reasons, characterizing the centrality of nodes in multiplex networks and finding new ways to solve challenging inference problems defined on multiplex networks are fundamental questions of network science. In this paper, we discuss the relevance of the Multiplex PageRank algorithm for measuring the centrality of nodes in multilayer networks and we characterize the utility of the recently introduced indicator function Θ̃(S) for describing their mesoscale organization and community structure. As working examples for studying these measures, we consider three multiplex network datasets coming for social science.

  16. Extracting Information from Multiplex Networks

    CERN Document Server

    Iacovacci, Jacopo

    2016-01-01

    Multiplex networks are generalized network structures that are able to describe networks in which the same set of nodes are connected by links that have different connotations. Multiplex networks are ubiquitous since they describe social, financial, engineering and biological networks as well. Extending our ability to analyze complex networks to multiplex network structures increases greatly the level of information that is possible to extract from Big Data. For these reasons characterizing the centrality of nodes in multiplex networks and finding new ways to solve challenging inference problems defined on multiplex networks are fundamental questions of network science. In this paper we discuss the relevance of the Multiplex PageRank algorithm for measuring the centrality of nodes in multilayer networks and we characterize the utility of the recently introduced indicator function $\\widetilde{\\Theta}^{S}$ for describing their mesoscale organization and community structure. As working examples for studying thes...

  17. Extracting information from multiplex networks

    Science.gov (United States)

    Iacovacci, Jacopo; Bianconi, Ginestra

    2016-06-01

    Multiplex networks are generalized network structures that are able to describe networks in which the same set of nodes are connected by links that have different connotations. Multiplex networks are ubiquitous since they describe social, financial, engineering, and biological networks as well. Extending our ability to analyze complex networks to multiplex network structures increases greatly the level of information that is possible to extract from big data. For these reasons, characterizing the centrality of nodes in multiplex networks and finding new ways to solve challenging inference problems defined on multiplex networks are fundamental questions of network science. In this paper, we discuss the relevance of the Multiplex PageRank algorithm for measuring the centrality of nodes in multilayer networks and we characterize the utility of the recently introduced indicator function Θ ˜ S for describing their mesoscale organization and community structure. As working examples for studying these measures, we consider three multiplex network datasets coming for social science.

  18. Generic information can retrieve known biological associations: implications for biomedical knowledge discovery.

    Directory of Open Access Journals (Sweden)

    Herman H H B M van Haagen

    Full Text Available MOTIVATION: Weighted semantic networks built from text-mined literature can be used to retrieve known protein-protein or gene-disease associations, and have been shown to anticipate associations years before they are explicitly stated in the literature. Our text-mining system recognizes over 640,000 biomedical concepts: some are specific (i.e., names of genes or proteins others generic (e.g., 'Homo sapiens'. Generic concepts may play important roles in automated information retrieval, extraction, and inference but may also result in concept overload and confound retrieval and reasoning with low-relevance or even spurious links. Here, we attempted to optimize the retrieval performance for protein-protein interactions (PPI by filtering generic concepts (node filtering or links to generic concepts (edge filtering from a weighted semantic network. First, we defined metrics based on network properties that quantify the specificity of concepts. Then using these metrics, we systematically filtered generic information from the network while monitoring retrieval performance of known protein-protein interactions. We also systematically filtered specific information from the network (inverse filtering, and assessed the retrieval performance of networks composed of generic information alone. RESULTS: Filtering generic or specific information induced a two-phase response in retrieval performance: initially the effects of filtering were minimal but beyond a critical threshold network performance suddenly drops. Contrary to expectations, networks composed exclusively of generic information demonstrated retrieval performance comparable to unfiltered networks that also contain specific concepts. Furthermore, an analysis using individual generic concepts demonstrated that they can effectively support the retrieval of known protein-protein interactions. For instance the concept "binding" is indicative for PPI retrieval and the concept "mutation abnormality" is

  19. Proposal for a new LEIR Slow Extraction Scheme dedicated to Biomedical Research

    CERN Document Server

    Garonna, A; Carli, C

    2014-01-01

    This report presents a proposal for a new slow extraction scheme for the Low Energy Ion Ring (LEIR) in the context of the feasibility study for a biomedical research facility at CERN. LEIR has to be maintained as a heavy ion accumulator ring for LHC and for fixed-target experiments with the SPS. In parallel to this on-going operation for physics experiments, an additional secondary use of LEIR for a biomedical research facility was proposed [Dosanjh2013, Holzscheiter2012, PHE2010]. This facility would complement the existing research beam-time available at other laboratories for studies related to ion beam therapy. The new slow extraction [Abler2013] is based on the third-integer resonance. The reference beam is composed of fully stripped carbon ions with extraction energies of 20-440 MeV/u, transverse physical emittances of 5-25 µm and momentum spreads of ±2-9•10-4. Two resonance driving mechanisms have been studied: the quadrupole-driven method and the RF-knockout technique. Both were made compatible...

  20. PASSIM – an open source software system for managing information in biomedical studies

    Directory of Open Access Journals (Sweden)

    Neogi Sudeshna

    2007-02-01

    Full Text Available Abstract Background One of the crucial aspects of day-to-day laboratory information management is collection, storage and retrieval of information about research subjects and biomedical samples. An efficient link between sample data and experiment results is absolutely imperative for a successful outcome of a biomedical study. Currently available software solutions are largely limited to large-scale, expensive commercial Laboratory Information Management Systems (LIMS. Acquiring such LIMS indeed can bring laboratory information management to a higher level, but often implies sufficient investment of time, effort and funds, which are not always available. There is a clear need for lightweight open source systems for patient and sample information management. Results We present a web-based tool for submission, management and retrieval of sample and research subject data. The system secures confidentiality by separating anonymized sample information from individuals' records. It is simple and generic, and can be customised for various biomedical studies. Information can be both entered and accessed using the same web interface. User groups and their privileges can be defined. The system is open-source and is supplied with an on-line tutorial and necessary documentation. It has proven to be successful in a large international collaborative project. Conclusion The presented system closes the gap between the need and the availability of lightweight software solutions for managing information in biomedical studies involving human research subjects.

  1. Strategies for Disseminating Information on Biomedical Research on Autism to Hispanic Parents

    Science.gov (United States)

    Lajonchere, Clara M.; Wheeler, Barbara Y.; Valente, Thomas W.; Kreutzer, Cary; Munson, Aron; Narayanan, Shrikanth; Kazemzadeh, Abe; Cruz, Roxana; Martinez, Irene; Schrager, Sheree M.; Schweitzer, Lisa; Chklovski, Tara; Hwang, Darryl

    2016-01-01

    Low income Hispanic families experience multiple barriers to accessing evidence-based information on Autism Spectrum Disorders (ASD). This study utilized a mixed-strategy intervention to create access to information in published bio-medical research articles on ASD by distilling the content into parent-friendly English- and Spanish-language ASD…

  2. Personalized Web Services for Web Information Extraction

    CERN Document Server

    Jarir, Zahi; Erradi, Mahammed

    2011-01-01

    The field of information extraction from the Web emerged with the growth of the Web and the multiplication of online data sources. This paper is an analysis of information extraction methods. It presents a service oriented approach for web information extraction considering both web data management and extraction services. Then we propose an SOA based architecture to enhance flexibility and on-the-fly modification of web extraction services. An implementation of the proposed architecture is proposed on the middleware level of Java Enterprise Edition (JEE) servers.

  3. Cloud computing: a new business paradigm for biomedical information sharing.

    Science.gov (United States)

    Rosenthal, Arnon; Mork, Peter; Li, Maya Hao; Stanford, Jean; Koester, David; Reynolds, Patti

    2010-04-01

    We examine how the biomedical informatics (BMI) community, especially consortia that share data and applications, can take advantage of a new resource called "cloud computing". Clouds generally offer resources on demand. In most clouds, charges are pay per use, based on large farms of inexpensive, dedicated servers, sometimes supporting parallel computing. Substantial economies of scale potentially yield costs much lower than dedicated laboratory systems or even institutional data centers. Overall, even with conservative assumptions, for applications that are not I/O intensive and do not demand a fully mature environment, the numbers suggested that clouds can sometimes provide major improvements, and should be seriously considered for BMI. Methodologically, it was very advantageous to formulate analyses in terms of component technologies; focusing on these specifics enabled us to bypass the cacophony of alternative definitions (e.g., exactly what does a cloud include) and to analyze alternatives that employ some of the component technologies (e.g., an institution's data center). Relative analyses were another great simplifier. Rather than listing the absolute strengths and weaknesses of cloud-based systems (e.g., for security or data preservation), we focus on the changes from a particular starting point, e.g., individual lab systems. We often find a rough parity (in principle), but one needs to examine individual acquisitions--is a loosely managed lab moving to a well managed cloud, or a tightly managed hospital data center moving to a poorly safeguarded cloud?

  4. Ontology-based retrieval of bio-medical information based on microarray text corpora

    DEFF Research Database (Denmark)

    Hansen, Kim Allan; Zambach, Sine; Have, Christian Theil

    Microarray technology is often used in gene expression exper- iments. Information retrieval in the context of microarrays has mainly been concerned with the analysis of the numeric data produced; how- ever, the experiments are often annotated with textual metadata. Al- though biomedical resources...... degree. We explore the possibilities of retrieving biomedical information from microarrays in Gene Expression Omnibus (GEO), of which we have indexed a sample semantically, as a rst step towards ontology based searches. Through an example we argue that it is possible to improve the retrieval...

  5. Biomedical Information Extraction: Mining Disease Associated Genes from Literature

    Science.gov (United States)

    Huang, Zhong

    2014-01-01

    Disease associated gene discovery is a critical step to realize the future of personalized medicine. However empirical and clinical validation of disease associated genes are time consuming and expensive. In silico discovery of disease associated genes from literature is therefore becoming the first essential step for biomarker discovery to…

  6. BOAT: automatic alignment of biomedical ontologies using term informativeness and candidate selection.

    Science.gov (United States)

    Chua, Watson Wei Khong; Kim, Jung-Jae

    2012-04-01

    The biomedical sciences is one of the few domains where ontologies are widely being developed to facilitate information retrieval and knowledge sharing, but there still remains the problem that applications using different ontologies cannot share knowledge without explicit references between overlapping concepts. Ontology alignment is the task of identifying such equivalence relations between concepts across ontologies. Its application to the biomedical domain should address two open issues: (1) determining the equivalence of concept-pairs which have overlapping terms in their names, and (2) the high run-time required to align large ontologies which are typical in the biomedical domain. To address them, we present a novel approach, named the Biomedical Ontologies Alignment Technique (BOAT), which is state-of-the-art in terms of F-measure, precision and speed. A key feature of BOAT is that it considers the informativeness of each component word in the concept labels, which has significant impact on biomedical ontologies, resulting in a 12.2% increase in F-measure. Another important feature of BOAT is that it selects for comparison only concept pairs that show high likelihoods of equivalence, based on the similarity of their annotations. BOAT's F-measure of 0.88 for the alignment of the mouse and human anatomy ontologies is on par with that of another state-of-the-art matcher, AgreementMaker, while taking a shorter time.

  7. Use of a systematic review to inform the infection risk for biomedical engineers and technicians servicing biomedical devices.

    Science.gov (United States)

    Smith, Anne-Louise

    2011-12-01

    Many microorganisms responsible for hospital-acquired infections are able to stay viable on surfaces with no visible sign of contamination, in dry conditions and on non-porous surfaces. The infection risk to biomedical staff when servicing biomedical devices is not documented. An indirect approach has been used to examine the different aspects that will affect the risk of infection including a systematic review of microbial contamination and transmission relating to biomedical devices. A systematic review found 58% of biomedical devices have microbial contamination with 13% having at least one pathogenic organism. These microbes can persist for some months. Occupational-infections of biomedical service staff are low compared to other healthcare workers. A biomedical device with contaminated surface or dust was identified as the source of patient outbreaks in 13 papers. The cleaning agent most tested for removal of micro-organisms from devices was alcohol swabs, but sterile water swabs were also effective. However, manufacturers mainly recommend (74%) cleaning devices with water and detergent. Biomedical engineers and technicians have a small risk of being exposed to dangerous micro-organisms on most biomedical devices, but without skin breakage, this exposure is unlikely to cause ill-health. It is recommended that biomedical staff follow good infection control practices, wipe devices with detergent, sterile water or alcohol swabs as recommended by the manufacturer before working on them, and keep alcohol hand rubs accessible at all benches.

  8. Extracting microRNA-gene relations from biomedical literature using distant supervision

    Science.gov (United States)

    Clarke, Luka A.; Couto, Francisco M.

    2017-01-01

    Many biomedical relation extraction approaches are based on supervised machine learning, requiring an annotated corpus. Distant supervision aims at training a classifier by combining a knowledge base with a corpus, reducing the amount of manual effort necessary. This is particularly useful for biomedicine because many databases and ontologies have been made available for many biological processes, while the availability of annotated corpora is still limited. We studied the extraction of microRNA-gene relations from text. MicroRNA regulation is an important biological process due to its close association with human diseases. The proposed method, IBRel, is based on distantly supervised multi-instance learning. We evaluated IBRel on three datasets, and the results were compared with a co-occurrence approach as well as a supervised machine learning algorithm. While supervised learning outperformed on two of those datasets, IBRel obtained an F-score 28.3 percentage points higher on the dataset for which there was no training set developed specifically. To demonstrate the applicability of IBRel, we used it to extract 27 miRNA-gene relations from recently published papers about cystic fibrosis. Our results demonstrate that our method can be successfully used to extract relations from literature about a biological process without an annotated corpus. The source code and data used in this study are available at https://github.com/AndreLamurias/IBRel. PMID:28263989

  9. Extraction and Characterization of Collagen from Buffalo Skin for Biomedical Applications

    Directory of Open Access Journals (Sweden)

    Moustafa A. Rizk

    2016-06-01

    Full Text Available Collagen is widely used for biomedical and pharmaceutical applications due to its excellent biocompatibility, biodegradability and weak antigenicity. However, applicability is limited due to its high cost and probability of disease transmission from the current sources, which are bovine and porcine. In the present study, collagen was extracted from 6 months buffalo skins as alternative save sources. Collagen was characterized by different physico-chemical techniques like ATR-FTIR, Raman, SEM, DSC and amino acids analysis. Proline and hydroxyproline contents of buffalo skin collagen were higher than those of calf skin collagen. Thermal stability of buffalo skin collagen is high with respect to that of calf skin collagen. The obtained buffalo skin collagen shows higher stiffness upon cross-linking with glutaraldehyde. Thus buffalo skin collagen can be used for fabrication of high strength bioactive sponge and sheets for medical applications, like scaffold for tissue engineering, drug delivery and wound dressing system.

  10. Information- Theoretic Analysis for the Difficulty of Extracting Hidden Information

    Institute of Scientific and Technical Information of China (English)

    ZHANG Wei-ming; LI Shi-qu; CAO Jia; LIU Jiu-fen

    2005-01-01

    The difficulty of extracting hidden information,which is essentially a kind of secrecy, is analyzed by information-theoretic method. The relations between key rate, message rate, hiding capacity and difficulty of extraction are studied in the terms of unicity distance of stego-key, and the theoretic conclusion is used to analyze the actual extracting attack on Least Significant Bit(LSB) steganographic algorithms.

  11. Toward a fully de-identified biomedical information warehouse.

    Science.gov (United States)

    Liu, Jianhua; Erdal, Selnur; Silvey, Scott A; Ding, Jing; Riedel, John D; Marsh, Clay B; Kamal, Jyoti

    2009-11-14

    The Information Warehouse at the Ohio State University Medical Center is a comprehensive repository of business, clinical, and research data from various source systems. Data collected here is a valuable resource that facilitates both translational research and personalized healthcare. The use of such data in research is governed by federal privacy regulations with oversight by the Institutional Review Board. In 2006, the Information Warehouse was recognized by the OSU IRB as an "Honest Broker" of clinical data, providing investigators with de-identified or limited datasets under stipulations contained in a signed data use agreement. In order to streamline this process even further, the Information Warehouse is developing a de-identified data warehouse that is suitable for direct user access through a controlled query tool that is aimed to support both research and education activities. In this paper we report our findings on performance evaluation of different de-identification schemes that may be used to ensure regulatory compliance while also facilitating practical database updating and querying. We also discuss how date-shifting in the de-identification process can impact other data elements such as diagnosis and procedure codes and consider a possible solution to those problems.

  12. Discovering biomedical semantic relations in PubMed queries for information retrieval and database curation.

    Science.gov (United States)

    Huang, Chung-Chi; Lu, Zhiyong

    2016-01-01

    Identifying relevant papers from the literature is a common task in biocuration. Most current biomedical literature search systems primarily rely on matching user keywords. Semantic search, on the other hand, seeks to improve search accuracy by understanding the entities and contextual relations in user keywords. However, past research has mostly focused on semantically identifying biological entities (e.g. chemicals, diseases and genes) with little effort on discovering semantic relations. In this work, we aim to discover biomedical semantic relations in PubMed queries in an automated and unsupervised fashion. Specifically, we focus on extracting and understanding the contextual information (or context patterns) that is used by PubMed users to represent semantic relations between entities such as 'CHEMICAL-1 compared to CHEMICAL-2' With the advances in automatic named entity recognition, we first tag entities in PubMed queries and then use tagged entities as knowledge to recognize pattern semantics. More specifically, we transform PubMed queries into context patterns involving participating entities, which are subsequently projected to latent topics via latent semantic analysis (LSA) to avoid the data sparseness and specificity issues. Finally, we mine semantically similar contextual patterns or semantic relations based on LSA topic distributions. Our two separate evaluation experiments of chemical-chemical (CC) and chemical-disease (CD) relations show that the proposed approach significantly outperforms a baseline method, which simply measures pattern semantics by similarity in participating entities. The highest performance achieved by our approach is nearly 0.9 and 0.85 respectively for the CC and CD task when compared against the ground truth in terms of normalized discounted cumulative gain (nDCG), a standard measure of ranking quality. These results suggest that our approach can effectively identify and return related semantic patterns in a ranked order

  13. Enhanced Pattern Representation in Information Extraction

    Institute of Scientific and Technical Information of China (English)

    廖乐健; 曹元大; 张映波

    2004-01-01

    Traditional pattern representation in information extraction lack in the ability of representing domain-specific concepts and are therefore devoid of flexibility. To overcome these restrictions, an enhanced pattern representation is designed which includes ontological concepts, neighboring-tree structures and soft constraints. An information-extraction inference engine based on hypothesis-generation and conflict-resolution is implemented. The proposed technique is successfully applied to an information extraction system for Chinese-language query front-end of a job-recruitment search engine.

  14. [Biomedical information on the internet using search engines. A one-year trial].

    Science.gov (United States)

    Corrao, Salvatore; Leone, Francesco; Arnone, Sabrina

    2004-01-01

    The internet is a communication medium and content distributor that provide information in the general sense but it could be of great utility regarding as the search and retrieval of biomedical information. Search engines represent a great deal to rapidly find information on the net. However, we do not know whether general search engines and meta-search ones are reliable in order to find useful and validated biomedical information. The aim of our study was to verify the reproducibility of a search by key-words (pediatric or evidence) using 9 international search engines and 1 meta-search engine at the baseline and after a one year period. We analysed the first 20 citations as output of each searching. We evaluated the formal quality of Web-sites and their domain extensions. Moreover, we compared the output of each search at the start of this study and after a one year period and we considered as a criterion of reliability the number of Web-sites cited again. We found some interesting results that are reported throughout the text. Our findings point out an extreme dynamicity of the information on the Web and, for this reason, we advice a great caution when someone want to use search and meta-search engines as a tool for searching and retrieve reliable biomedical information. On the other hand, some search and meta-search engines could be very useful as a first step searching for defining better a search and, moreover, for finding institutional Web-sites too. This paper allows to know a more conscious approach to the internet biomedical information universe.

  15. An integrated biomedical knowledge extraction and analysis platform: using federated search and document clustering technology.

    Science.gov (United States)

    Taylor, Donald P

    2007-01-01

    High content screening (HCS) requires time-consuming and often complex iterative information retrieval and assessment approaches to optimally conduct drug discovery programs and biomedical research. Pre- and post-HCS experimentation both require the retrieval of information from public as well as proprietary literature in addition to structured information assets such as compound libraries and projects databases. Unfortunately, this information is typically scattered across a plethora of proprietary bioinformatics tools and databases and public domain sources. Consequently, single search requests must be presented to each information repository, forcing the results to be manually integrated for a meaningful result set. Furthermore, these bioinformatics tools and data repositories are becoming increasingly complex to use; typically they fail to allow for more natural query interfaces. Vivisimo has developed an enterprise software platform to bridge disparate silos of information. The platform automatically categorizes search results into descriptive folders without the use of taxonomies to drive the categorization. A new approach to information retrieval for HCS experimentation is proposed.

  16. Organization of Biomedical Data for Collaborative Scientific Research: A Research Information Management System

    Science.gov (United States)

    Myneni, Sahiti; Patel, Vimla L.

    2010-01-01

    Biomedical researchers often work with massive, detailed and heterogeneous datasets. These datasets raise new challenges of information organization and management for scientific interpretation, as they demand much of the researchers’ time and attention. The current study investigated the nature of the problems that researchers face when dealing with such data. Four major problems identified with existing biomedical scientific information management methods were related to data organization, data sharing, collaboration, and publications. Therefore, there is a compelling need to develop an efficient and user-friendly information management system to handle the biomedical research data. This study evaluated the implementation of an information management system, which was introduced as part of the collaborative research to increase scientific productivity in a research laboratory. Laboratory members seemed to exhibit frustration during the implementation process. However, empirical findings revealed that they gained new knowledge and completed specified tasks while working together with the new system. Hence, researchers are urged to persist and persevere when dealing with any new technology, including an information management system in a research laboratory environment. PMID:20543892

  17. Organization of Biomedical Data for Collaborative Scientific Research: A Research Information Management System.

    Science.gov (United States)

    Myneni, Sahiti; Patel, Vimla L

    2010-06-01

    Biomedical researchers often work with massive, detailed and heterogeneous datasets. These datasets raise new challenges of information organization and management for scientific interpretation, as they demand much of the researchers' time and attention. The current study investigated the nature of the problems that researchers face when dealing with such data. Four major problems identified with existing biomedical scientific information management methods were related to data organization, data sharing, collaboration, and publications. Therefore, there is a compelling need to develop an efficient and user-friendly information management system to handle the biomedical research data. This study evaluated the implementation of an information management system, which was introduced as part of the collaborative research to increase scientific productivity in a research laboratory. Laboratory members seemed to exhibit frustration during the implementation process. However, empirical findings revealed that they gained new knowledge and completed specified tasks while working together with the new system. Hence, researchers are urged to persist and persevere when dealing with any new technology, including an information management system in a research laboratory environment.

  18. Efficient Techniques of Sparse Signal Analysis for Enhanced Recovery of Information in Biomedical Engineering and Geosciences

    KAUST Repository

    Sana, Furrukh

    2016-11-01

    Sparse signals are abundant among both natural and man-made signals. Sparsity implies that the signal essentially resides in a small dimensional subspace. The sparsity of the signal can be exploited to improve its recovery from limited and noisy observations. Traditional estimation algorithms generally lack the ability to take advantage of signal sparsity. This dissertation considers several problems in the areas of biomedical engineering and geosciences with the aim of enhancing the recovery of information by exploiting the underlying sparsity in the problem. The objective is to overcome the fundamental bottlenecks, both in terms of estimation accuracies and required computational resources. In the first part of dissertation, we present a high precision technique for the monitoring of human respiratory movements by exploiting the sparsity of wireless ultra-wideband signals. The proposed technique provides a novel methodology of overcoming the Nyquist sampling constraint and enables robust performance in the presence of noise and interferences. We also present a comprehensive framework for the important problem of extracting the fetal electrocardiogram (ECG) signals from abdominal ECG recordings of pregnant women. The multiple measurement vectors approach utilized for this purpose provides an efficient mechanism of exploiting the common structure of ECG signals, when represented in sparse transform domains, and allows leveraging information from multiple ECG electrodes under a joint estimation formulation. In the second part of dissertation, we adopt sparse signal processing principles for improved information recovery in large-scale subsurface reservoir characterization problems. We propose multiple new algorithms for sparse representation of the subsurface geological structures, incorporation of useful prior information in the estimation process, and for reducing computational complexities of the problem. The techniques presented here enable significantly

  19. Biosynthesis of silver nanoparticle from leaf extract of Desmodium gangeticum (L.) DC. and its biomedical potential

    Science.gov (United States)

    Thirunavoukkarasu, M.; Balaji, U.; Behera, S.; Panda, P. K.; Mishra, B. K.

    2013-12-01

    An aqueous leaf extract of Desmodium gangeticum was employed to synthesize silver nano particles. Rapid formation of stable silver nanoparticles were observed on exposure of the aqueous leaf extract with solution of silver nitrate. The silver nanoparticles were characterized by UV-visible spectroscopy, scanning electron microscopy, energy dispersive X-ray analysis and transmission electron microscopy (TEM), and Fourier Transform Infra-Red spectroscopy (FTIR) UV-visible spectroscopy, scanning electron microscopy (SEM), energy dispersive X-ray analysis (EDAX), transmission electron microscopy (TEM), and Fourier Transform Infra-Red spectroscopy (FTIR). UV-visible spectrum of the aqueous medium peaked at 450 nm corresponding to the plasmon absorbance of silver nanoparticles. SEM analysis revealed the spherical shape of the particles with sizes ranging from 18 to 39 nm and the EDAX spectrum confirmed the presence of silver along with other elements in the plant metabolite. Further, these biologically synthesized nanoparticles were found to be highly toxic against pathogenic bacteria Escherichia coli, thus implying significance of the present study in production of biomedical products.

  20. Information Extraction From Chemical Patents

    Directory of Open Access Journals (Sweden)

    Sandra Bergmann

    2012-01-01

    Full Text Available The development of new chemicals or pharmaceuticals is preceded by an indepth analysis of published patents in this field. This information retrieval is a costly and time inefficient step when done by a human reader, yet it is mandatory for potential success of an investment. The goal of the research project UIMA-HPC is to automate and hence speed-up the process of knowledge mining about patents. Multi-threaded analysis engines, developed according to UIMA (Unstructured Information Management Architecture standards, process texts and images in thousands of documents in parallel. UNICORE (UNiform Interface to COmputing Resources workflow control structures make it possible to dynamically allocate resources for every given task to gain best cpu-time/realtime ratios in an HPC environment.

  1. A System for Information Management in BioMedical Studies—SIMBioMS

    Science.gov (United States)

    Krestyaninova, Maria; Zarins, Andris; Viksna, Juris; Kurbatova, Natalja; Rucevskis, Peteris; Neogi, Sudeshna Guha; Gostev, Mike; Perheentupa, Teemu; Knuuttila, Juha; Barrett, Amy; Lappalainen, Ilkka; Rung, Johan; Podnieks, Karlis; Sarkans, Ugis; McCarthy, Mark I; Brazma, Alvis

    2009-01-01

    Summary: SIMBioMS is a web-based open source software system for managing data and information in biomedical studies. It provides a solution for the collection, storage, management and retrieval of information about research subjects and biomedical samples, as well as experimental data obtained using a range of high-throughput technologies, including gene expression, genotyping, proteomics and metabonomics. The system can easily be customized and has proven to be successful in several large-scale multi-site collaborative projects. It is compatible with emerging functional genomics data standards and provides data import and export in accepted standard formats. Protocols for transferring data to durable archives at the European Bioinformatics Institute have been implemented. Availability: The source code, documentation and initialization scripts are available at http://simbioms.org. Contact: support@simbioms.org; mariak@ebi.ac.uk PMID:19633095

  2. Chrysopogon zizanioides aqueous extract mediated synthesis, characterization of crystalline silver and gold nanoparticles for biomedical applications.

    Science.gov (United States)

    Arunachalam, Kantha D; Annamalai, Sathesh Kumar

    2013-01-01

    The exploitation of various plant materials for the biosynthesis of nanoparticles is considered a green technology as it does not involve any harmful chemicals. The aim of this study was to develop a simple biological method for the synthesis of silver and gold nanoparticles using Chrysopogon zizanioides. To exploit various plant materials for the biosynthesis of nanoparticles was considered a green technology. An aqueous leaf extract of C. zizanioides was used to synthesize silver and gold nanoparticles by the bioreduction of silver nitrate (AgNO3) and chloroauric acid (HAuCl4) respectively. Water-soluble organics present in the plant materials were mainly responsible for reducing silver or gold ions to nanosized Ag or Au particles. The synthesized silver and gold nanoparticles were characterized by ultraviolet (UV)-visible spectroscopy, scanning electron microscopy (SEM), energy dispersive X-ray analysis (EDAX), Fourier transform infrared spectroscopy (FTIR), and X-ray diffraction (XRD) analysis. The kinetics decline reactions of aqueous silver/gold ion with the C. zizanioides crude extract were determined by UV-visible spectroscopy. SEM analysis showed that aqueous gold ions, when exposed to the extract were reduced and resulted in the biosynthesis of gold nanoparticles in the size range 20-50 nm. This eco-friendly approach for the synthesis of nanoparticles is simple, can be scaled up for large-scale production with powerful bioactivity as demonstrated by the synthesized silver nanoparticles. The synthesized nanoparticles can have clinical use as antibacterial, antioxidant, as well as cytotoxic agents and can be used for biomedical applications.

  3. Chrysopogon zizanioides aqueous extract mediated synthesis characterization of crystalline silver and gold nanoparticles for biomedical applications

    Directory of Open Access Journals (Sweden)

    Arunachalam KD

    2013-07-01

    Full Text Available Kantha D Arunachalam, Sathesh Kumar Annamalai Center for Environmental Nuclear Research, Directorate of Research, SRM University, Chennai, Tamil Nadu, India Abstract: The exploitation of various plant materials for the biosynthesis of nanoparticles is considered a green technology as it does not involve any harmful chemicals. The aim of this study was to develop a simple biological method for the synthesis of silver and gold nanoparticles using Chrysopogon zizanioides. To exploit various plant materials for the biosynthesis of nanoparticles was considered a green technology. An aqueous leaf extract of C. zizanioides was used to synthesize silver and gold nanoparticles by the bioreduction of silver nitrate (AgNO3 and chloroauric acid (HAuCl4 respectively. Water-soluble organics present in the plant materials were mainly responsible for reducing silver or gold ions to nanosized Ag or Au particles. The synthesized silver and gold nanoparticles were characterized by ultraviolet (UV-visible spectroscopy, scanning electron microscopy (SEM, energy dispersive X-ray analysis (EDAX, Fourier transform infrared spectroscopy (FTIR, and X-ray diffraction (XRD analysis. The kinetics decline reactions of aqueous silver/gold ion with the C. zizanioides crude extract were determined by UV-visible spectroscopy. SEM analysis showed that aqueous gold ions, when exposed to the extract were reduced and resulted in the biosynthesis of gold nanoparticles in the size range 20–50 nm. This eco-friendly approach for the synthesis of nanoparticles is simple, can be scaled up for large-scale production with powerful bioactivity as demonstrated by the synthesized silver nanoparticles. The synthesized nanoparticles can have clinical use as antibacterial, antioxidant, as well as cytotoxic agents and can be used for biomedical applications. Keywords: nanoparticles, bioreduction, SEM, silver, gold

  4. Application of GIS to Geological Information Extraction

    Institute of Scientific and Technical Information of China (English)

    2000-01-01

    GIS. a powerful tool for processing spatial data, is advantageous in its spatial overlaying. In this paper, GIS is applied to the extraction of geological information. Information associated with mineral resources is chosen to delineate the geo-anomalies, the basis of ore-forming anomalies and of mineral-deposit location. This application is illustrated with an example in Weixi area, Yunnan Province.

  5. Implementation and management of a biomedical observation dictionary in a large healthcare information system

    Science.gov (United States)

    Vandenbussche, Pierre-Yves; Cormont, Sylvie; André, Christophe; Daniel, Christel; Delahousse, Jean; Charlet, Jean; Lepage, Eric

    2013-01-01

    Objective This study shows the evolution of a biomedical observation dictionary within the Assistance Publique Hôpitaux Paris (AP-HP), the largest European university hospital group. The different steps are detailed as follows: the dictionary creation, the mapping to logical observation identifier names and codes (LOINC), the integration into a multiterminological management platform and, finally, the implementation in the health information system. Methods AP-HP decided to create a biomedical observation dictionary named AnaBio, to map it to LOINC and to maintain the mapping. A management platform based on methods used for knowledge engineering has been put in place. It aims at integrating AnaBio within the health information system and improving both the quality and stability of the dictionary. Results This new management platform is now active in AP-HP. The AnaBio dictionary is shared by 120 laboratories and currently includes 50 000 codes. The mapping implementation to LOINC reaches 40% of the AnaBio entries and uses 26% of LOINC records. The results of our work validate the choice made to develop a local dictionary aligned with LOINC. Discussion and Conclusions This work constitutes a first step towards a wider use of the platform. The next step will support the entire biomedical production chain, from the clinician prescription, through laboratory tests tracking in the laboratory information system to the communication of results and the use for decision support and biomedical research. In addition, the increase in the mapping implementation to LOINC ensures the interoperability allowing communication with other international health institutions. PMID:23635601

  6. Data integration and knowledge discovery in biomedical databases. Reliable information from unreliable sources

    Directory of Open Access Journals (Sweden)

    A Mitnitski

    2003-01-01

    Full Text Available To better understand information about human health from databases we analyzed three datasets collected for different purposes in Canada: a biomedical database of older adults, a large population survey across all adult ages, and vital statistics. Redundancy in the variables was established, and this led us to derive a generalized (macroscopic state variable, being a fitness/frailty index that reflects both individual and group health status. Evaluation of the relationship between fitness/frailty and the mortality rate revealed that the latter could be expressed in terms of variables generally available from any cross-sectional database. In practical terms, this means that the risk of mortality might readily be assessed from standard biomedical appraisals collected for other purposes.

  7. Automated Extraction Of Associations Between Methylated Genes and Diseases From Biomedical Literature

    KAUST Repository

    Bin Res, Arwa A.

    2012-12-01

    Associations between methylated genes and diseases have been investigated in several studies, and it is critical to have such information available for better understanding of diseases and clinical decisions. However, such information is scattered in a large number of electronic publications and it is difficult to manually search for it. Therefore, the goal of the project is to develop a machine learning model that can efficiently extract such information. Twelve machine learning algorithms were applied and compared in application to this problem based on three approaches that involve: document-term frequency matrices, position weight matrices, and a hybrid approach that uses the combination of the previous two. The best results we obtained by the hybrid approach with a random forest model that, in a 10-fold cross-validation, achieved F-score and accuracy of nearly 85% and 84%, respectively. On a completely separate testing set, F-score and accuracy of 89% and 88%, respectively, were obtained. Based on this model, we developed a tool that automates extraction of associations between methylated genes and diseases from electronic text. Our study contributed an efficient method for extracting specific types of associations from free text and the methodology developed here can be extended to other similar association extraction problems.

  8. Semantics-driven modelling of user preferences for information retrieval in the biomedical domain.

    Science.gov (United States)

    Gladun, Anatoly; Rogushina, Julia; Valencia-García, Rafael; Béjar, Rodrigo Martínez

    2013-03-01

    A large amount of biomedical and genomic data are currently available on the Internet. However, data are distributed into heterogeneous biological information sources, with little or even no organization. Semantic technologies provide a consistent and reliable basis with which to confront the challenges involved in the organization, manipulation and visualization of data and knowledge. One of the knowledge representation techniques used in semantic processing is the ontology, which is commonly defined as a formal and explicit specification of a shared conceptualization of a domain of interest. The work presented here introduces a set of interoperable algorithms that can use domain and ontological information to improve information-retrieval processes. This work presents an ontology-based information-retrieval system for the biomedical domain. This system, with which some experiments have been carried out that are described in this paper, is based on the use of domain ontologies for the creation and normalization of lightweight ontologies that represent user preferences in a determined domain in order to improve information-retrieval processes.

  9. A service-oriented distributed semantic mediator: integrating multiscale biomedical information.

    Science.gov (United States)

    Mora, Oscar; Engelbrecht, Gerhard; Bisbal, Jesus

    2012-11-01

    Biomedical research continuously generates large amounts of heterogeneous and multimodal data spread over multiple data sources. These data, if appropriately shared and exploited, could dramatically improve the research practice itself, and ultimately the quality of health care delivered. This paper presents DISMED (DIstributed Semantic MEDiator), an open source semantic mediator that provides a unified view of a federated environment of multiscale biomedical data sources. DISMED is a Web-based software application to query and retrieve information distributed over a set of registered data sources, using semantic technologies. It also offers a userfriendly interface specifically designed to simplify the usage of these technologies by non-expert users. Although the architecture of the software mediator is generic and domain independent, in the context of this paper, DISMED has been evaluated for managing biomedical environments and facilitating research with respect to the handling of scientific data distributed in multiple heterogeneous data sources. As part of this contribution, a quantitative evaluation framework has been developed. It consist of a benchmarking scenario and the definition of five realistic use-cases. This framework, created entirely with public datasets, has been used to compare the performance of DISMED against other available mediators. It is also available to the scientific community in order to evaluate progress in the domain of semantic mediation, in a systematic and comparable manner. The results show an average improvement in the execution time by DISMED of 55% compared to the second best alternative in four out of the five use-cases of the experimental evaluation.

  10. Extraction of information from a single quantum

    OpenAIRE

    Paraoanu, G. S.

    2011-01-01

    We investigate the possibility of performing quantum tomography on a single qubit with generalized partial measurements and the technique of measurement reversal. Using concepts from statistical decision theory, we prove that, somewhat surprisingly, no information can be obtained using this scheme. It is shown that, irrespective of the measurement technique used, extraction of information from single quanta is at odds with other general principles of quantum physics.

  11. DKIE: Open Source Information Extraction for Danish

    DEFF Research Database (Denmark)

    Derczynski, Leon; Field, Camilla Vilhelmsen; Bøgh, Kenneth Sejdenfaden

    2014-01-01

    Danish is a major Scandinavian language spoken daily by around six million people. However, it lacks a unified, open set of NLP tools. This demonstration will introduce DKIE, an extensible open-source toolkit for processing Danish text. We implement an information extraction architecture for Danish...... independently or with the Stanford NLP toolkit....

  12. Web Information Extraction%Web信息抽取

    Institute of Scientific and Technical Information of China (English)

    李晶; 陈恩红

    2003-01-01

    With the tremendous amount of information available on the Web, the ability to quickly obtain information has become a crucial problem. It is not enough for us to acquire information only with Web information retrieval technology. Therefore more and more people pay attention to Web information extraction technology. This paper first in- troduces some concepts of information extraction technology, then introduces and analyzes several typical Web information extraction methods based on the differences in extraction patterns.

  13. Visualization of the Meridian System Based on Biomedical Information about Acupuncture Treatment

    Directory of Open Access Journals (Sweden)

    In-Seon Lee

    2013-01-01

    Full Text Available The origin of the concept of the meridian system is closely connected with the treatment effects of acupuncture, and it serves as an empirical reference system in the clinical setting. Understanding the meridian channels would be a first step in enhancing the clinical efficacy of acupuncture treatment. To understand the relationship between the location of the disease and the sites of relevant acupoints, we investigated acupuncture treatment regimens for low-back pain in 37 clinical studies. We found that the most frequently used acupoints in the treatment of low-back pain were BL23 (51%, BL25 (43%, BL24 (32%, BL40 (32%, BL60 (32%, GB30 (32%, BL26 (28%, BL32 (28%, and GB34 (21%. For the example of low-back pain, we visualized the biomedical information (frequency rates about acupuncture treatment on the meridians of a three-dimensional (3D model of the human body. We found that both local and distal acupoints were used to treat low-back pain in clinical trials based on the meridian theory. We suggest a new model for the visualization of a data-driven 3D meridian system of biomedical information about the meridians and acupoints. These findings may be helpful in understanding the meridian system and revealing the effectiveness of acupuncture treatment.

  14. Automated information extraction from web APIs documentation

    OpenAIRE

    Ly, Papa Alioune; Pedrinaci, Carlos; Domingue, John

    2012-01-01

    A fundamental characteristic of Web APIs is the fact that, de facto, providers hardly follow any standard practices while implementing, publishing, and documenting their APIs. As a consequence, the discovery and use of these services by third parties is significantly hampered. In order to achieve further automation while exploiting Web APIs we present an approach for automatically extracting relevant technical information from the Web pages documenting them. In particular we have devised two ...

  15. Information extraction and CT reconstruction of liver images based on diffraction enhanced imaging

    Institute of Scientific and Technical Information of China (English)

    Chunhong Hu; Tao Zhao; Lu Zhang; Hui Li; Xinyan Zhao; Shuqian Luo

    2009-01-01

    X-ray phase-contrast imaging (PCI) is a new emerging imaging technique that generates a high spatial resolution and high contrast of biological soft tissues compared to conventional radiography. Herein a biomedical application of diffraction enhanced imaging (DEI) is presented. As one of the PCI methods, DEI derives contrast from many different kinds of sample information, such as the sample's X-ray absorption, refraction gradient and ultra-small-angle X-ray scattering (USAXS) properties, and the sample information is expressed by three parametric images. Combined with computed tomography (CT), DEI-CT can produce 3D volumetric images of the sample and can be used for investigating micro-structures of biomedical samples. Our DEI experiments for fiver samples were implemented at the topog-raphy station of Beijing Synchrotron Radiation Facility (BSRF). The results show that by using our provided information extraction method and DEI-CT reconstruction approach, the obtained parametric images clearly display the inner structures of liver tissues and the morphology of blood vessels. Furthermore, the reconstructed 3D view of the fiver blood vessels exhibits the micro blood vessels whose minimum diameter is on the order of about tens of microns, much better than its conventional CT reconstruction at a millimeter resolution.In conclusion, both the information extraction method and DEI-CT have the potential for use in biomedical micro-structures analysis.

  16. Unsupervised information extraction by text segmentation

    CERN Document Server

    Cortez, Eli

    2013-01-01

    A new unsupervised approach to the problem of Information Extraction by Text Segmentation (IETS) is proposed, implemented and evaluated herein. The authors' approach relies on information available on pre-existing data to learn how to associate segments in the input string with attributes of a given domain relying on a very effective set of content-based features. The effectiveness of the content-based features is also exploited to directly learn from test data structure-based features, with no previous human-driven training, a feature unique to the presented approach. Based on the approach, a

  17. Extracting the information backbone in online system

    CERN Document Server

    Zhang, Qian-Ming; Shang, Ming-Sheng

    2013-01-01

    Information overload is a serious problem in modern society and many solutions such as recommender system have been proposed to filter out irrelevant information. In the literature, researchers mainly dedicated to improve the recommendation performance (accuracy and diversity) of the algorithms while overlooked the influence of topology of the online user-object bipartite networks. In this paper, we find that some information provided by the bipartite networks is not only redundant but also misleading. With such "less can be more" feature, we design some algorithms to improve the recommendation performance by eliminating some links from the original networks. Moreover, we propose a hybrid method combining the time-aware and topology-aware link removal algorithms to extract the backbone which contains the essential information for the recommender systems. From the practical point of view, our method can improve the performance and reduce the computational time of the recommendation system, thus improve both of...

  18. Extracting the information backbone in online system.

    Science.gov (United States)

    Zhang, Qian-Ming; Zeng, An; Shang, Ming-Sheng

    2013-01-01

    Information overload is a serious problem in modern society and many solutions such as recommender system have been proposed to filter out irrelevant information. In the literature, researchers have been mainly dedicated to improving the recommendation performance (accuracy and diversity) of the algorithms while they have overlooked the influence of topology of the online user-object bipartite networks. In this paper, we find that some information provided by the bipartite networks is not only redundant but also misleading. With such "less can be more" feature, we design some algorithms to improve the recommendation performance by eliminating some links from the original networks. Moreover, we propose a hybrid method combining the time-aware and topology-aware link removal algorithms to extract the backbone which contains the essential information for the recommender systems. From the practical point of view, our method can improve the performance and reduce the computational time of the recommendation system, thus improving both of their effectiveness and efficiency.

  19. Supporting effective health and biomedical information retrieval and navigation: a novel facet view interface evaluation.

    Science.gov (United States)

    Mu, Xiangming; Ryu, Hohyon; Lu, Kun

    2011-08-01

    There is a need to provide a more effective user interface to facilitate non-domain experts' health information seeking in authoritative online databases such as MEDLINE. We developed a new topic cluster based information navigation system called SimMed. Instead of offering a list of documents, SimMed presents users with a list of ranked clusters. Topically similar documents are grouped together to provide users with a better overview of the search results and to support exploration of similar literature within a cluster. We conducted an empirical user study to compare SimMed to a traditional document list based search interface. A total of 42 study participants were recruited to use both interfaces for health information exploration search tasks. The results showed that SimMed is more effective in terms of users' perceived topic knowledge changes and their engagement in user-system interactions. We also developed a new metric to assess users' efforts to find relevant citations. On average, users need significantly fewer clicks to find relevant information in SimMed than in the baseline system. Comments from study participants indicated that SimMed is more helpful in finding similar citations, providing related medical terms, and presenting better organized search results, particularly when the initial search is unsatisfactory. Findings from the study shed light on future health and biomedical information retrieval system and interface designs.

  20. Digital image processing for information extraction.

    Science.gov (United States)

    Billingsley, F. C.

    1973-01-01

    The modern digital computer has made practical image processing techniques for handling nonlinear operations in both the geometrical and the intensity domains, various types of nonuniform noise cleanup, and the numerical analysis of pictures. An initial requirement is that a number of anomalies caused by the camera (e.g., geometric distortion, MTF roll-off, vignetting, and nonuniform intensity response) must be taken into account or removed to avoid their interference with the information extraction process. Examples illustrating these operations are discussed along with computer techniques used to emphasize details, perform analyses, classify materials by multivariate analysis, detect temporal differences, and aid in human interpretation of photos.

  1. Extraction of information from unstructured text

    Energy Technology Data Exchange (ETDEWEB)

    Irwin, N.H.; DeLand, S.M.; Crowder, S.V.

    1995-11-01

    Extracting information from unstructured text has become an emphasis in recent years due to the large amount of text now electronically available. This status report describes the findings and work done by the end of the first year of a two-year LDRD. Requirements of the approach included that it model the information in a domain independent way. This means that it would differ from current systems by not relying on previously built domain knowledge and that it would do more than keyword identification. Three areas that are discussed and expected to contribute to a solution include (1) identifying key entities through document level profiling and preprocessing, (2) identifying relationships between entities through sentence level syntax, and (3) combining the first two with semantic knowledge about the terms.

  2. Inverse problem for biomedical applications: use of prior information on target and forward model parameters

    Science.gov (United States)

    Martelli, Fabrizio; Del Bianco, Samuele; Zaccanti, Giovanni

    2011-02-01

    We propose the use of a retrieval operator for biomedical applications in near-infrared spectroscopy. The proposed retrieval operator is based on the "Optimal Estimation" method. The main characteristic of this method relates to the possibility to include prior information both on target and on forward model parameters of the inversion procedure. The possibility of the retrieval operator to elaborate a-priori information can in principle be a benefit for the whole retrieval procedure. This means that a larger number of target parameters can be retrieved, or that a better accuracy can be achieved in retrieving the target parameters. The final goal of this inversion procedure is to have an improved estimate of the target parameters. The procedure has been tested on time-resolved simulated experiments obtained with a Monte Carlo code. The results obtained show that an improved performance of the inversion procedure is achieved when prior information on target and forward model parameters is available. With the use of a priori information on target parameters we have in average a lower difference between the retrieved values of the parameters and their true values, and the error bars determined by the inversion procedure on the retrieved parameters are significantly lower. At the same time a good estimate of the errors on the forward model parameters can significantly improve the retrieval of the target parameters.

  3. Extracting the information backbone in online system.

    Directory of Open Access Journals (Sweden)

    Qian-Ming Zhang

    Full Text Available Information overload is a serious problem in modern society and many solutions such as recommender system have been proposed to filter out irrelevant information. In the literature, researchers have been mainly dedicated to improving the recommendation performance (accuracy and diversity of the algorithms while they have overlooked the influence of topology of the online user-object bipartite networks. In this paper, we find that some information provided by the bipartite networks is not only redundant but also misleading. With such "less can be more" feature, we design some algorithms to improve the recommendation performance by eliminating some links from the original networks. Moreover, we propose a hybrid method combining the time-aware and topology-aware link removal algorithms to extract the backbone which contains the essential information for the recommender systems. From the practical point of view, our method can improve the performance and reduce the computational time of the recommendation system, thus improving both of their effectiveness and efficiency.

  4. The caCORE Software Development Kit: Streamlining construction of interoperable biomedical information services

    Directory of Open Access Journals (Sweden)

    Warzel Denise

    2006-01-01

    Full Text Available Abstract Background Robust, programmatically accessible biomedical information services that syntactically and semantically interoperate with other resources are challenging to construct. Such systems require the adoption of common information models, data representations and terminology standards as well as documented application programming interfaces (APIs. The National Cancer Institute (NCI developed the cancer common ontologic representation environment (caCORE to provide the infrastructure necessary to achieve interoperability across the systems it develops or sponsors. The caCORE Software Development Kit (SDK was designed to provide developers both within and outside the NCI with the tools needed to construct such interoperable software systems. Results The caCORE SDK requires a Unified Modeling Language (UML tool to begin the development workflow with the construction of a domain information model in the form of a UML Class Diagram. Models are annotated with concepts and definitions from a description logic terminology source using the Semantic Connector component. The annotated model is registered in the Cancer Data Standards Repository (caDSR using the UML Loader component. System software is automatically generated using the Codegen component, which produces middleware that runs on an application server. The caCORE SDK was initially tested and validated using a seven-class UML model, and has been used to generate the caCORE production system, which includes models with dozens of classes. The deployed system supports access through object-oriented APIs with consistent syntax for retrieval of any type of data object across all classes in the original UML model. The caCORE SDK is currently being used by several development teams, including by participants in the cancer biomedical informatics grid (caBIG program, to create compatible data services. caBIG compatibility standards are based upon caCORE resources, and thus the caCORE SDK has

  5. Extraction of quantifiable information from complex systems

    CERN Document Server

    Dahmen, Wolfgang; Griebel, Michael; Hackbusch, Wolfgang; Ritter, Klaus; Schneider, Reinhold; Schwab, Christoph; Yserentant, Harry

    2014-01-01

    In April 2007, the  Deutsche Forschungsgemeinschaft (DFG) approved the  Priority Program 1324 “Mathematical Methods for Extracting Quantifiable Information from Complex Systems.” This volume presents a comprehensive overview of the most important results obtained over the course of the program.   Mathematical models of complex systems provide the foundation for further technological developments in science, engineering and computational finance.  Motivated by the trend toward steadily increasing computer power, ever more realistic models have been developed in recent years. These models have also become increasingly complex, and their numerical treatment poses serious challenges.   Recent developments in mathematics suggest that, in the long run, much more powerful numerical solution strategies could be derived if the interconnections between the different fields of research were systematically exploited at a conceptual level. Accordingly, a deeper understanding of the mathematical foundations as w...

  6. Biomedical Applications of the Information-efficient Spectral Imaging Sensor (ISIS)

    Energy Technology Data Exchange (ETDEWEB)

    Gentry, S.M.; Levenson, R.

    1999-01-21

    The Information-efficient Spectral Imaging Sensor (ISIS) approach to spectral imaging seeks to bridge the gap between tuned multispectral and fixed hyperspectral imaging sensors. By allowing the definition of completely general spectral filter functions, truly optimal measurements can be made for a given task. These optimal measurements significantly improve signal-to-noise ratio (SNR) and speed, minimize data volume and data rate, while preserving classification accuracy. The following paper investigates the application of the ISIS sensing approach in two sample biomedical applications: prostate and colon cancer screening. It is shown that in these applications, two to three optimal measurements are sufficient to capture the majority of classification information for critical sample constituents. In the prostate cancer example, the optimal measurements allow 8% relative improvement in classification accuracy of critical cell constituents over a red, green, blue (RGB) sensor. In the colon cancer example, use of optimal measurements boost the classification accuracy of critical cell constituents by 28% relative to the RGB sensor. In both cases, optimal measurements match the performance achieved by the entire hyperspectral data set. The paper concludes that an ISIS style spectral imager can acquire these optimal spectral images directly, allowing improved classification accuracy over an RGB sensor. Compared to a hyperspectral sensor, the ISIS approach can achieve similar classification accuracy using a significantly lower number of spectral samples, thus minimizing overall sample classification time and cost.

  7. SEMANTIC INFORMATION EXTRACTION IN UNIVERSITY DOMAIN

    Directory of Open Access Journals (Sweden)

    Swathi

    2012-07-01

    Full Text Available Today’s conventional search engines hardly do provide the essential content relevant to the user’s search query. This is because the context and semantics of the request made by the user is not analyzed to the full extent. So here the need for a semantic web search arises. SWS is upcoming in the area of web search which combines Natural Language Processing and Artificial Intelligence. The objective of the work done here is to design, develop and implement a semantic search engine- SIEU(Semantic Information Extraction in University Domain confined to the university domain. SIEU uses ontology as a knowledge base for the information retrieval process. It is not just a mere keyword search. It is one layer above what Google or any other search engines retrieve by analyzing just the keywords. Here the query is analyzed both syntactically and semantically. The developed system retrieves the web results more relevant to the user query through keyword expansion. The results obtained here will be accurate enough to satisfy the request made by the user. The level of accuracy will be enhanced since the query is analyzed semantically. The system will be of great use to the developers and researchers who work on web. The Google results are re-ranked and optimized for providing the relevant links. For ranking an algorithm has been applied which fetches more apt results for the user query.

  8. From Waste to Healing Biopolymers: Biomedical Applications of Bio-Collagenic Materials Extracted from Industrial Leather Residues in Wound Healing

    Directory of Open Access Journals (Sweden)

    Rafael Luque

    2013-04-01

    Full Text Available The biomedical properties of a porous bio-collagenic polymer extracted from leather industrial waste residues have been investigated in wound healing and tissue regeneration in induced wounds in rats. Application of the pure undiluted bio-collagen to induced wounds in rats dramatically improved its healing after 7 days in terms of collagen production and wound filling as well as in the migration and differentiation of keratinocytes. The formulation tested was found to be three times more effective than the commercial reference product Catrix® (Heal Progress (HP: 8 ± 1.55 vs. 2.33 ± 0.52, p < 0.001; Formation of Collagen (FC: 7.5 ± 1.05 vs. 2.17 ± 0.75, p < 0.001; Regeneration of Epidermis (RE: 13.33 ± 5.11 vs. 5 ± 5.48, p < 0.05.

  9. eClims: An Extensible and Dynamic Integration Framework for Biomedical Information Systems.

    Science.gov (United States)

    Savonnet, Marinette; Leclercq, Eric; Naubourg, Pierre

    2016-11-01

    Biomedical information systems (BIS) require consideration of three types of variability: data variability induced by new high throughput technologies, schema or model variability induced by large scale studies or new fields of research, and knowledge variability resulting from new discoveries. Beyond data heterogeneity, managing variabilities in the context of BIS requires extensible and dynamic integration process. In this paper, we focus on data and schema variabilities and we propose an integration framework based on ontologies, master data, and semantic annotations. The framework addresses issues related to: 1) collaborative work through a dynamic integration process; 2) variability among studies using an annotation mechanism; and 3) quality control over data and semantic annotations. Our approach relies on two levels of knowledge: BIS-related knowledge is modeled using an application ontology coupled with UML models that allow controlling data completeness and consistency, and domain knowledge is described by a domain ontology, which ensures data coherence. A system build with the eClims framework has been implemented and evaluated in the context of a proteomic platform.

  10. CONAN : Text Mining in the Biomedical Domain

    NARCIS (Netherlands)

    Malik, R.

    2006-01-01

    This thesis is about Text Mining. Extracting important information from literature. In the last years, the number of biomedical articles and journals is growing exponentially. Scientists might not find the information they want because of the large number of publications. Therefore a system was cons

  11. Method for Extracting Product Information from TV Commercial

    Directory of Open Access Journals (Sweden)

    Kohei Arai

    2011-09-01

    Full Text Available Television (TV Commercial program contains important product information that displayed only in seconds. People who need that information has no insufficient time for noted it, even just for reading that information. This research work focus on automatically detect text and extract important information from a TV commercial to provide information in real time and for video indexing. We propose method for product information extraction from TV commercial using knowledge based system with pattern matching rule based method. Implementation and experiments on 50 commercial screenshot images achieved a high accuracy result on text extraction and information recognition.

  12. Bio-medical (EMG Signal Analysis and Feature Extraction Using Wavelet Transform

    Directory of Open Access Journals (Sweden)

    Rhutuja Raut

    2015-03-01

    Full Text Available In this paper, the multi-channel electromyogram acquisition system is being developed using programmable system on chip (PSOC microcontroller to obtain the surface of EMG signal. The two pairs of single-channel surface electrodes are utilized to measure the EMG signal obtained from forearm muscles. Then different levels of Wavelet family are used to analyze the EMG signal. Later features in terms of root mean square, logarithm of root mean square, centroid of frequency, as well as standard deviation were used to extract the EMG signal. The proposed method of feature extraction for extracting EMG signal states that root means square feature extraction method gives better performance as compared to the other features. In the near future, this method can be used to control a mechanical arm as well as robotic arm in field of real-time processing.

  13. Respiratory Information Extraction from Electrocardiogram Signals

    KAUST Repository

    Amin, Gamal El Din Fathy

    2010-12-01

    The Electrocardiogram (ECG) is a tool measuring the electrical activity of the heart, and it is extensively used for diagnosis and monitoring of heart diseases. The ECG signal reflects not only the heart activity but also many other physiological processes. The respiratory activity is a prominent process that affects the ECG signal due to the close proximity of the heart and the lungs. In this thesis, several methods for the extraction of respiratory process information from the ECG signal are presented. These methods allow an estimation of the lung volume and the lung pressure from the ECG signal. The potential benefit of this is to eliminate the corresponding sensors used to measure the respiration activity. A reduction of the number of sensors connected to patients will increase patients’ comfort and reduce the costs associated with healthcare. As a further result, the efficiency of diagnosing respirational disorders will increase since the respiration activity can be monitored with a common, widely available method. The developed methods can also improve the detection of respirational disorders that occur while patients are sleeping. Such disorders are commonly diagnosed in sleeping laboratories where the patients are connected to a number of different sensors. Any reduction of these sensors will result in a more natural sleeping environment for the patients and hence a higher sensitivity of the diagnosis.

  14. Information Extraction on the Web with Credibility Guarantee

    OpenAIRE

    Nguyen, Thanh Tam

    2015-01-01

    The Web became the central medium for valuable sources of information extraction applications. However, such user-generated resources are often plagued by inaccuracies and misinformation due to the inherent openness and uncertainty of the Web. In this work we study the problem of extracting structured information out of Web data with a credibility guarantee. The ultimate goal is that not only the structured information should be extracted as much as possible but also its credibility is high. ...

  15. User-centered evaluation of Arizona BioPathway: an information extraction, integration, and visualization system.

    Science.gov (United States)

    Quiñones, Karin D; Su, Hua; Marshall, Byron; Eggers, Shauna; Chen, Hsinchun

    2007-09-01

    Explosive growth in biomedical research has made automated information extraction, knowledge integration, and visualization increasingly important and critically needed. The Arizona BioPathway (ABP) system extracts and displays biological regulatory pathway information from the abstracts of journal articles. This study uses relations extracted from more than 200 PubMed abstracts presented in a tabular and graphical user interface with built-in search and aggregation functionality. This paper presents a task-centered assessment of the usefulness and usability of the ABP system focusing on its relation aggregation and visualization functionalities. Results suggest that our graph-based visualization is more efficient in supporting pathway analysis tasks and is perceived as more useful and easier to use as compared to a text-based literature-viewing method. Relation aggregation significantly contributes to knowledge-acquisition efficiency. Together, the graphic and tabular views in the ABP Visualizer provide a flexible and effective interface for pathway relation browsing and analysis. Our study contributes to pathway-related research and biological information extraction by assessing the value of a multiview, relation-based interface that supports user-controlled exploration of pathway information across multiple granularities.

  16. A Study of the Information Literacy of Biomedical Graduate Students: Based on the Thesis Topic Discovery Process in Molecular Biology Research

    Directory of Open Access Journals (Sweden)

    Jhao-Yen Huang

    2014-06-01

    Full Text Available The biomedical information environment is in a state of constant and rapid change due to the increase in research data and rapid technological advances. In Taiwan, few research has investigated the information literacy of biomedical graduate students. This exploratory study examined the information literacy abilities and training of biomedical graduate students in Taiwan. Semi-structured interviews based on the Association of College and Research Libraries Information Literacy Competency Standards for Science and Engineering/Technology were conducted with 20 molecular biological graduate students. The interview inquired about their information-seeking channels and information literacy education. The findings show that the biomedical graduate students developed a workable thesis topic with their advisors. Through various information-seeking channels and retrieval strategies, they obtained and critically evaluated information to address different information needs for their thesis research. Through seminars, annual conferences and papers, the interviewees were informed of current developments in their field. Subsequently, through written or oral communications, they were able to integrate and exchange the information. Most interviewees cared about the social, economic, legal, and ethical issues surrounding the use of information. College courses and labs were the main information literacy education environment for them to learn about research skills and knowledge. The study concludes four areas to address for the information literacy of biomedical graduate students, i.e., using professional information, using the current information, efficiency in assessing the domain information, and utilization of diverse information channels. Currently, the interviewees showed rather low usage of library resources, which is a concern for biomedical educators and libraries. [Article content in Chinese

  17. Information Extraction Using Distant Supervision and Semantic Similarities

    Directory of Open Access Journals (Sweden)

    PARK, Y.

    2016-02-01

    Full Text Available Information extraction is one of the main research tasks in natural language processing and text mining that extracts useful information from unstructured sentences. Information extraction techniques include named entity recognition, relation extraction, and co-reference resolution. Among them, relation extraction refers to a task that extracts semantic relations between entities such as personal and geographic names in documents. This is an important research area, which is used in knowledge base construction and question and answering systems. This study presents relation extraction using a distant supervision learning technique among semi-supervised learning methods, which have been spotlighted in recent years to reduce human manual work and costs required for supervised learning. That is, this study proposes a method that can improve relation extraction by improving a distant supervision learning technique by applying a clustering method to create a learning corpus and semantic analysis for relation extraction that is difficult to identify using existing distant supervision. Through comparison experiments of various semantic similarity comparison methods, similarity calculation methods that are useful to relation extraction using distant supervision are searched, and a large number of accurate relation triples can be extracted using the proposed structural advantages and semantic similarity comparison.

  18. A biomedical information system for retrieval and manipulation of NHANES data.

    Science.gov (United States)

    Mukherjee, Sukrit; Martins, David; Norris, Keith C; Jenders, Robert A

    2013-01-01

    The retrieval and manipulation of data from large public databases like the U.S. National Health and Nutrition Examination Survey (NHANES) may require sophisticated statistical software and significant expertise that may be unavailable in the university setting. In response, we have developed the Data Retrieval And Manipulation System (DReAMS), an automated information system to handle all processes of data extraction and cleaning and then joining different subsets to produce analysis-ready output. The system is a browser-based data warehouse application in which the input data from flat files or operational systems are aggregated in a structured way so that the desired data can be read, recoded, queried and extracted efficiently. The current pilot implementation of the system provides access to a limited amount of NHANES database. We plan to increase the amount of data available through the system in the near future and to extend the techniques to other large databases from CDU archive with a current holding of about 53 databases.

  19. Pattern information extraction from crystal structures

    OpenAIRE

    Okuyan, Erhan

    2005-01-01

    Cataloged from PDF version of article. Determining crystal structure parameters of a material is a quite important issue in crystallography. Knowing the crystal structure parameters helps to understand physical behavior of material. For complex structures, particularly for materials which also contain local symmetry as well as global symmetry, obtaining crystal parameters can be quite hard. This work provides a tool that will extract crystal parameters such as primitive vect...

  20. Re-ranking with context for high-performance biomedical information retrieval.

    Science.gov (United States)

    Yin, Xiaoshi; Huang, Jimmy Xiangji; Li, Zhoujun

    2012-01-01

    In this paper, we present a context-sensitive approach to re-ranking retrieved documents for further improving the effectiveness of high-performance biomedical literature retrieval systems. For each topic, a two-dimensional positive context is learnt from the top N retrieved documents and a group of negative contexts are learnt from the last N' documents in initial retrieval ranked list. The contextual space contains lexical context and conceptual context. The probabilities that retrieved documents are generated within the contextual space are then computed for document re-ranking. Empirical evaluation on the TREC Genomics full-text collection and three high-performance biomedical literature retrieval runs demonstrates that the context-sensitive re-ranking approach yields better retrieval performance.

  1. Laurus nobilis leaf extract mediated green synthesis of ZnO nanoparticles: Characterization and biomedical applications.

    Science.gov (United States)

    Vijayakumar, Sekar; Vaseeharan, Baskaralingam; Malaikozhundan, Balasubramanian; Shobiya, Malaikkarasu

    2016-12-01

    The present study reports the green synthesis of zinc oxide nanoparticles using the aqueous leaf extract of Laurus nobilis (Ln-ZnO NPs) by co-precipitation method. The synthesized Ln-ZnO NPs were characterized by UV-Vis spectroscopy, FTIR, XRD, TEM, SEM and EDX. Ln-ZnO NPs were crystalline in nature, flower like and have hexagonal wurtzite structure with a mean particle size of 47.27nm. The antibacterial activity of Ln-ZnO NPs was greater against Gram positive (Staphylococcus aureus) bacteria than Gram negative (Pseudomonas aeruginosa) bacteria. The zone of inhibition against S. aureus was 11.4, 12.6 and 14.2mm at 25, 50 and 75μgmL(-1). The zone of inhibition against P. aeruginosa was 9.8, 10.2 and 11.3mm at 25, 50 and 75μgmL(-1). The light and confocal laser scanning microscopic images evidenced that Ln-ZnO NPs effectively inhibited the biofilm growth of S. aureus and P. aeruginosa at 75μgmL(-1). The cytotoxicity studies revealed that Ln-ZnO NPs showed no effect on normal murine RAW264.7 macrophage cells. On the other hand, Ln-ZnO NPs were effective in inhibiting the viability of human A549 lung cancer cells at higher concentrations of 80μgmL(-1). The morphological changes in the Ln-ZnO NPs treated A549 lung cancer cells were observed under phase contrast microscope.

  2. Source-specific Informative Prior for i-Vector Extraction

    DEFF Research Database (Denmark)

    Shepstone, Sven Ewan; Lee, Kong Aik; Li, Haizhou

    2015-01-01

    -informative, since for homogeneous datasets there is no gain in generality in using an informative prior. This work shows that extracting i-vectors for a heterogeneous dataset, containing speech samples recorded from multiple sources, using informative priors instead is applicable, and leads to favorable results...

  3. Changing the face of reference: adapting biomedical and health information services for the classroom, clinic, and beyond.

    Science.gov (United States)

    Tennant, Michele R; Auten, Beth; Botero, Cecilia E; Butson, Linda C; Edwards, Mary E; Garcia-Milian, Rolando; Lyon, Jennifer A; Norton, Hannah F

    2012-01-01

    This article describes how the reference department at a large academic health sciences library evolved to address the clinical and research information needs of the parent organization without losing its close connections to the classroom and curriculum. Closing the reference desk, moving to on-call and house call models, designing positions such as clinical research librarian and basic biomedical sciences librarian, finding alternative funding to grow the department, providing technology and training to facilitate librarians' work, and developing programming for and taking advice from library clients facilitated efforts to create a relevant presence and solidify the library's place in the university community.

  4. Can we replace curation with information extraction software?

    Science.gov (United States)

    Karp, Peter D

    2016-01-01

    Can we use programs for automated or semi-automated information extraction from scientific texts as practical alternatives to professional curation? I show that error rates of current information extraction programs are too high to replace professional curation today. Furthermore, current IEP programs extract single narrow slivers of information, such as individual protein interactions; they cannot extract the large breadth of information extracted by professional curators for databases such as EcoCyc. They also cannot arbitrate among conflicting statements in the literature as curators can. Therefore, funding agencies should not hobble the curation efforts of existing databases on the assumption that a problem that has stymied Artificial Intelligence researchers for more than 60 years will be solved tomorrow. Semi-automated extraction techniques appear to have significantly more potential based on a review of recent tools that enhance curator productivity. But a full cost-benefit analysis for these tools is lacking. Without such analysis it is possible to expend significant effort developing information-extraction tools that automate small parts of the overall curation workflow without achieving a significant decrease in curation costs.Database URL.

  5. Addressing Information Proliferation: Applications of Information Extraction and Text Mining

    Science.gov (United States)

    Li, Jingjing

    2013-01-01

    The advent of the Internet and the ever-increasing capacity of storage media have made it easy to store, deliver, and share enormous volumes of data, leading to a proliferation of information on the Web, in online libraries, on news wires, and almost everywhere in our daily lives. Since our ability to process and absorb this information remains…

  6. Integrating Information Extraction Agents into a Tourism Recommender System

    Science.gov (United States)

    Esparcia, Sergio; Sánchez-Anguix, Víctor; Argente, Estefanía; García-Fornes, Ana; Julián, Vicente

    Recommender systems face some problems. On the one hand information needs to be maintained updated, which can result in a costly task if it is not performed automatically. On the other hand, it may be interesting to include third party services in the recommendation since they improve its quality. In this paper, we present an add-on for the Social-Net Tourism Recommender System that uses information extraction and natural language processing techniques in order to automatically extract and classify information from the Web. Its goal is to maintain the system updated and obtain information about third party services that are not offered by service providers inside the system.

  7. Pattern information extraction from crystal structures

    Science.gov (United States)

    Okuyan, Erhan; Güdükbay, Uğur; Gülseren, Oğuz

    2007-04-01

    Determining the crystal structure parameters of a material is an important issue in crystallography and material science. Knowing the crystal structure parameters helps in understanding the physical behavior of material. It can be difficult to obtain crystal parameters for complex structures, particularly those materials that show local symmetry as well as global symmetry. This work provides a tool that extracts crystal parameters such as primitive vectors, basis vectors and space groups from the atomic coordinates of crystal structures. A visualization tool for examining crystals is also provided. Accordingly, this work could help crystallographers, chemists and material scientists to analyze crystal structures efficiently. Program summaryTitle of program: BilKristal Catalogue identifier: ADYU_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/ADYU_v1_0 Program obtainable from: CPC Program Library, Queen's University of Belfast, N. Ireland Licensing provisions: None Programming language used: C, C++, Microsoft .NET Framework 1.1 and OpenGL Libraries Computer: Personal Computers with Windows operating system Operating system: Windows XP Professional RAM: 20-60 MB No. of lines in distributed program, including test data, etc.:899 779 No. of bytes in distributed program, including test date, etc.:9 271 521 Distribution format:tar.gz External routines/libraries: Microsoft .NET Framework 1.1. For visualization tool, graphics card driver should also support OpenGL Nature of problem: Determining crystal structure parameters of a material is a quite important issue in crystallography. Knowing the crystal structure parameters helps to understand physical behavior of material. For complex structures, particularly, for materials which also contain local symmetry as well as global symmetry, obtaining crystal parameters can be quite hard. Solution method: The tool extracts crystal parameters such as primitive vectors, basis vectors and identify the space group from

  8. Mining knowledge from text repositories using information extraction: A review

    Indian Academy of Sciences (India)

    Sandeep R Sirsat; Dr Vinay Chavan; Dr Shrinivas P Deshpande

    2014-02-01

    There are two approaches to mining text form online repositories. First, when the knowledge to be discovered is expressed directly in the documents to be mined, Information Extraction (IE) alone can serve as an effective tool for such text mining. Second, when the documents contain concrete data in unstructured form rather than abstract knowledge, Information Extraction (IE) can be used to first transform the unstructured data in the document corpus into a structured database, and then use some state-of-the-art data mining algorithms/tools to identify abstract patterns in this extracted data. This paper presents the review of several methods related to these two approaches.

  9. Secure information embedding into 1D biomedical signals based on SPIHT.

    Science.gov (United States)

    Rubio, Oscar J; Alesanco, Alvaro; García, José

    2013-08-01

    This paper proposes an encoding system for 1D biomedical signals that allows embedding metadata and provides security and privacy. The design is based on the analysis of requirements for secure and efficient storage, transmission and access to medical tests in e-health environment. This approach uses the 1D SPIHT algorithm to compress 1D biomedical signals with clinical quality, metadata embedding in the compressed domain to avoid extra distortion, digital signature to implement security and attribute-level encryption to support Role-Based Access Control. The implementation has been extensively tested using standard electrocardiogram and electroencephalogram databases (MIT-BIH Arrhythmia, MIT-BIH Compression and SCCN-EEG), demonstrating high embedding capacity (e.g. 3 KB in resting ECGs, 200 KB in stress tests, 30 MB in ambulatory ECGs), short delays (2-3.3s in real-time transmission) and compression of the signal (by ≃3 in real-time transmission, by ≃5 in offline operation) despite of the embedding of security elements and metadata to enable e-health services.

  10. Improving information extraction using a probability-based approach

    DEFF Research Database (Denmark)

    Kim, S.; Ahmed, Saeema; Wallace, K.

    2007-01-01

    or retire. It is becoming essential to retrieve vital information from archived product documents, if it is available. There is, therefore, great interest in ways of extracting relevant and sharable information from documents. A keyword-based search is commonly used, but studies have shown...

  11. The study of the extraction of 3-D informations

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Min Ki [Korea Univ., Seoul (Korea); Kim, Jin Hun; Kim, Hui Yung; Lee, Gi Sik; Lee, Yung Shin [Sokyung Univ., Seoul (Korea)

    1998-04-01

    To extract three dimensional information in 3 dimensional real world two methods are applied (stereo image method, virtual reality environment method). 1. Stereo image method. From the paris of stereo image matching methods are applied to find the corresponding points in the two images. To solve the problem various methods are applied 2. Virtual reality environment method. As an alternate method to extract 3-D information, virtual reality environment is use. It is very useful to fine 6 DOF for a some given target points in 3-D space. We considered the accuracies and reliability of the 3-D informations. 34 figs., 4 tabs. (Author)

  12. Quantifying spectral changes experienced by plasmonic nanoparticles in a cellular environment to inform biomedical nanoparticle design

    Science.gov (United States)

    Chen, Allen L.; Hu, Ying S.; Jackson, Meredith A.; Lin, Adam Y.; Young, Joseph K.; Langsner, Robert J.; Drezek, Rebekah A.

    2014-08-01

    Metal nanoparticles (NPs) scatter and absorb light in precise, designable ways, making them agile candidates for a variety of biomedical applications. When NPs are introduced to a physiological environment and interact with cells, their physicochemical properties can change as proteins adsorb on their surface and they agglomerate within intracellular endosomal vesicles. Since the plasmonic properties of metal NPs are dependent on their geometry and local environment, these physicochemical changes may alter the NPs' plasmonic properties, on which applications such as plasmonic photothermal therapy and photonic gene circuits are based. Here we systematically study and quantify how metal NPs' optical spectra change upon introduction to a cellular environment in which NPs agglomerate within endosomal vesicles. Using darkfield hyperspectral imaging, we measure changes in the peak wavelength, broadening, and distribution of 100-nm spherical gold NPs' optical spectra following introduction to human breast adenocarcinoma Sk-Br-3 cells as a function of NP exposure dose and time. On a cellular level, spectra shift up to 78.6 ± 23.5 nm after 24 h of NP exposure. Importantly, spectra broaden with time, achieving a spectral width of 105.9 ± 11.7 nm at 95% of the spectrum's maximum intensity after 24 h. On an individual intracellular NP cluster (NPC) level, spectra also show significant shifting, broadening, and heterogeneity after 24 h. Cellular transmission electron microscopy (TEM) and electromagnetic simulations of NPCs support the trends in spectral changes we measured. These quantitative data can help guide the design of metal NPs introduced to cellular environments in plasmonic NP-mediated biomedical technologies.

  13. Extraction of Coupling Information From $Z' \\to jj$

    OpenAIRE

    Rizzo, T. G.

    1993-01-01

    An analysis by the ATLAS Collaboration has recently shown, contrary to popular belief, that a combination of strategic cuts, excellent mass resolution, and detailed knowledge of the QCD backgrounds from direct measurements can be used to extract a signal in the $Z' \\to jj$ channel in excess of $6\\sigma$ for certain classes of extended electroweak models. We explore the possibility that the data extracted from $Z$ dijet peak will have sufficient statistical power as to supply information on th...

  14. Biomedical data analysis by supervised manifold learning.

    Science.gov (United States)

    Alvarez-Meza, A M; Daza-Santacoloma, G; Castellanos-Dominguez, G

    2012-01-01

    Biomedical data analysis is usually carried out by assuming that the information structure embedded into the biomedical recordings is linear, but that statement actually does not corresponds to the real behavior of the extracted features. In order to improve the accuracy of an automatic system to diagnostic support, and to reduce the computational complexity of the employed classifiers, we propose a nonlinear dimensionality reduction methodology based on manifold learning with multiple kernel representations, which learns the underlying data structure of biomedical information. Moreover, our approach can be used as a tool that allows the specialist to do a visual analysis and interpretation about the studied variables describing the health condition. Obtained results show how our approach maps the original high dimensional features into an embedding space where simple and straightforward classification strategies achieve a suitable system performance.

  15. An automatic method for retrieving and indexing catalogues of biomedical courses.

    Science.gov (United States)

    Maojo, Victor; de la Calle, Guillermo; García-Remesal, Miguel; Bankauskaite, Vaida; Crespo, Jose

    2008-11-06

    Although there is wide information about Biomedical Informatics education and courses in different Websites, information is usually not exhaustive and difficult to update. We propose a new methodology based on information retrieval techniques for extracting, indexing and retrieving automatically information about educational offers. A web application has been developed to make available such information in an inventory of courses and educational offers.

  16. Rank Based Clustering For Document Retrieval From Biomedical Databases

    CERN Document Server

    Manicassamy, Jayanthi

    2009-01-01

    Now a day's, search engines are been most widely used for extracting information's from various resources throughout the world. Where, majority of searches lies in the field of biomedical for retrieving related documents from various biomedical databases. Currently search engines lacks in document clustering and representing relativeness level of documents extracted from the databases. In order to overcome these pitfalls a text based search engine have been developed for retrieving documents from Medline and PubMed biomedical databases. The search engine has incorporated page ranking bases clustering concept which automatically represents relativeness on clustering bases. Apart from this graph tree construction is made for representing the level of relatedness of the documents that are networked together. This advance functionality incorporation for biomedical document based search engine found to provide better results in reviewing related documents based on relativeness.

  17. Rank Based Clustering For Document Retrieval From Biomedical Databases

    Directory of Open Access Journals (Sweden)

    Jayanthi Manicassamy

    2009-09-01

    Full Text Available Now a day's, search engines are been most widely used for extracting information's from various resources throughout the world. Where, majority of searches lies in the field of biomedical for retrieving related documents from various biomedical databases. Currently search engines lacks in document clustering and representing relativeness level of documents extracted from the databases. In order to overcome these pitfalls a text based search engine have been developed for retrieving documents from Medline and PubMed biomedical databases. The search engine has incorporated page ranking bases clustering concept which automatically represents relativeness on clustering bases. Apart from this graph tree construction is made for representing the level of relatedness of the documents that are networked together. This advance functionality incorporation for biomedical document based search engine found to provide better results in reviewing related documents based on relativeness.

  18. Extracting clinical information to support medical decision based on standards.

    Science.gov (United States)

    Gomoi, Valentin; Vida, Mihaela; Stoicu-Tivadar, Lăcrămioara; Stoicu-Tivadar, Vasile

    2011-01-01

    The paper presents a method connecting medical databases to a medical decision system, and describes a service created to extract the necessary information that is transferred based on standards. The medical decision can be improved based on many inputs from different medical locations. The developed solution is described for a concrete case concerning the management for chronic pelvic pain, based on the information retrieved from diverse healthcare databases.

  19. Extracting an entanglement signature from only classical mutual information

    Energy Technology Data Exchange (ETDEWEB)

    Starling, David J.; Howell, John C. [Department of Physics and Astronomy, University of Rochester, Rochester, New York 14627 (United States); Broadbent, Curtis J. [Department of Physics and Astronomy, University of Rochester, Rochester, New York 14627 (United States); Rochester Theory Center, University of Rochester, Rochester, New York 14627 (United States)

    2011-09-15

    We introduce a quantity which is formed using classical notions of mutual information and which is computed using the results of projective measurements. This quantity constitutes a sufficient condition for entanglement and represents the amount of information that can be extracted from a bipartite system for spacelike separated observers. In addition to discussion, we provide simulations as well as experimental results for the singlet and maximally correlated mixed states.

  20. Extracting an entanglement signature from only classical mutual information

    Science.gov (United States)

    Starling, David J.; Broadbent, Curtis J.; Howell, John C.

    2011-09-01

    We introduce a quantity which is formed using classical notions of mutual information and which is computed using the results of projective measurements. This quantity constitutes a sufficient condition for entanglement and represents the amount of information that can be extracted from a bipartite system for spacelike separated observers. In addition to discussion, we provide simulations as well as experimental results for the singlet and maximally correlated mixed states.

  1. THE METHODS OF EXTRACTING WATER INFORMATION FROM SPOT IMAGE

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    Some techniques and methods for deriving water information from SPOT -4 (XI) image were investigatedand discussed in this paper. An algorithm of decision-tree (DT) classification which includes several classifiers based onthe spectral responding characteristics of water bodies and other objects, was developed and put forward to delineate wa-ter bodies. Another algorithm of decision-tree classification based on both spectral characteristics and auxiliary informa-tion of DEM and slope (DTDS) was also designed for water bodies extraction. In addition, supervised classificationmethod of maximum-likelyhood classification (MLC), and unsupervised method of interactive self-organizing dada analy-sis technique (ISODATA) were used to extract waterbodies for comparison purpose. An index was designed and used toassess the accuracy of different methods adopted in the research. Results have shown that water extraction accuracy wasvariable with respect to the various techniques applied. It was low using ISODATA, very high using DT algorithm andmuch higher using both DTDS and MLC.

  2. Efficient Retrieval of Text for Biomedical Domain using Expectation Maximization Algorithm

    Directory of Open Access Journals (Sweden)

    Sumit Vashishtha

    2011-11-01

    Full Text Available Data mining, a branch of computer science [1], is the process of extracting patterns from large data sets by combining methods from statistics and artificial intelligence with database management. Data mining is seen as an increasingly important tool by modern business to transform data into business intelligence giving an informational advantage. Biomedical text retrieval refers to text retrieval techniques applied to biomedical resources and literature available of the biomedical and molecular biology domain. The volume of published biomedical research, and therefore the underlying biomedical knowledge base, is expanding at an increasing rate. Biomedical text retrieval is a way to aid researchers in coping with information overload. By discovering predictive relationships between different pieces of extracted data, data-mining algorithms can be used to improve the accuracy of information extraction. However, textual variation due to typos, abbreviations, and other sources can prevent the productive discovery and utilization of hard-matching rules. Recent methods of soft clustering can exploit predictive relationships in textual data. This paper presents a technique for using soft clustering data mining algorithm to increase the accuracy of biomedical text extraction. Experimental results demonstrate that this approach improves text extraction more effectively that hard keyword matching rules.

  3. Spatiotemporal Information Extraction from a Historic Expedition Gazetteer

    Directory of Open Access Journals (Sweden)

    Mafkereseb Kassahun Bekele

    2016-11-01

    Full Text Available Historic expeditions are events that are flavored by exploratory, scientific, military or geographic characteristics. Such events are often documented in literature, journey notes or personal diaries. A typical historic expedition involves multiple site visits and their descriptions contain spatiotemporal and attributive contexts. Expeditions involve movements in space that can be represented by triplet features (location, time and description. However, such features are implicit and innate parts of textual documents. Extracting the geospatial information from these documents requires understanding the contextualized entities in the text. To this end, we developed a semi-automated framework that has multiple Information Retrieval and Natural Language Processing components to extract the spatiotemporal information from a two-volume historic expedition gazetteer. Our framework has three basic components, namely, the Text Preprocessor, the Gazetteer Processing Machine and the JAPE (Java Annotation Pattern Engine Transducer. We used the Brazilian Ornithological Gazetteer as an experimental dataset and extracted the spatial and temporal entities from entries that refer to three expeditioners’ site visits (which took place between 1910 and 1926 and mapped the trajectory of each expedition using the extracted information. Finally, one of the mapped trajectories was manually compared with a historical reference map of that expedition to assess the reliability of our framework.

  4. Tumor information extraction in radiology reports for hepatocellular carcinoma patients

    Science.gov (United States)

    Yim, Wen-wai; Denman, Tyler; Kwan, Sharon W.; Yetisgen, Meliha

    2016-01-01

    Hepatocellular carcinoma (HCC) is a deadly disease affecting the liver for which there are many available therapies. Targeting treatments towards specific patient groups necessitates defining patients by stage of disease. Criteria for such stagings include information on tumor number, size, and anatomic location, typically only found in narrative clinical text in the electronic medical record (EMR). Natural language processing (NLP) offers an automatic and scale-able means to extract this information, which can further evidence-based research. In this paper, we created a corpus of 101 radiology reports annotated for tumor information. Afterwards we applied machine learning algorithms to extract tumor information. Our inter-annotator partial match agreement scored at 0.93 and 0.90 F1 for entities and relations, respectively. Based on the annotated corpus, our sequential labeling entity extraction achieved 0.87 F1 partial match, and our maximum entropy classification relation extraction achieved scores 0.89 and 0. 74 F1 with gold and system entities, respectively. PMID:27570686

  5. Extending a geocoding database by Web information extraction

    Science.gov (United States)

    Wu, Yunchao; Niu, Zheng

    2008-10-01

    Local Search has recently attracted much attention. And the popular architecture of Local Search is map-and-hyperlinks, which links geo-referenced Web content to a map interface. This architecture shows that a good Local Search not only depends on search engine techniques, but also on a perfect geocoding database. The process of building and updating a geocoding database is laborious and time consuming so that it is usually difficult to keep up with the change of the real world. However, the Web provides a rich resource of location related information, which would be a supplementary information source for geocoding. Therefore, this paper introduces how to extract geographic information from Web documents to extend a geocoding database. Our approach involves two major steps. First, geographic named entities are identified and extracted from Web content. Then, named entities are geocoded and put into storage. By this way, we can extend a geocoding database to provide better local Web search services.

  6. The Study on Information Extraction Technology of Seismic Damage

    Directory of Open Access Journals (Sweden)

    Huang Zuo-wei

    2013-01-01

    Full Text Available In order to improve the information extraction technology of seismic damage assessment and information publishing of earthquake damage. Based on past earthquake experience it was constructed technical flow of earthquake damage assessment rapidly, this study, take Yushu earthquake as example, studies the framework and establishment of the information service system by means of Arc IMS and distributed database technology. It analysis some key technologies, build web publishing architecture of massive remote sensing images. The system implements joint application of remote sensing image processing technology, database technology and Web GIS technology, the result could provide the important basis for earthquake damage assessment, emergency management and rescue mission.

  7. Extraction of Information from Images using Dewrapping Techniques

    Directory of Open Access Journals (Sweden)

    Khalid Nazim S. A.

    2010-11-01

    Full Text Available An image containing textual information is called a document image. The textual information in document images is useful in areas like vehicle number plate reading, passport reading and cargo container reading and so on. Thus extracting useful textual information in the document image plays an important role in many applications. One of the major challenges in camera document analysis is to deal with the wrap and perspective distortions. In spite of the prevalence of dewrapping techniques, there is no standard efficient algorithm for the performance evaluation that concentrates on visualization. Wrapping is a common appearance document image before recognition. In order to capture the document images a mobile camera of 2megapixel resolution is used. A database is developed with variations in background, size and colour along with wrapped images, blurred and clean images. This database will be explored and text extraction from those document images is performed. In case of wrapped images no efficient dewrapping techniques have been implemented till date. Thus extracting the text from the wrapped images is done by maintaining a suitable template database. Further, the extracted text from the wrapped or other document images will be converted into an editable form such as Notepad or MS word document. The experimental results were corroborated on various objects of database.

  8. Extracting Semantic Information from Visual Data: A Survey

    Directory of Open Access Journals (Sweden)

    Qiang Liu

    2016-03-01

    Full Text Available The traditional environment maps built by mobile robots include both metric ones and topological ones. These maps are navigation-oriented and not adequate for service robots to interact with or serve human users who normally rely on the conceptual knowledge or semantic contents of the environment. Therefore, the construction of semantic maps becomes necessary for building an effective human-robot interface for service robots. This paper reviews recent research and development in the field of visual-based semantic mapping. The main focus is placed on how to extract semantic information from visual data in terms of feature extraction, object/place recognition and semantic representation methods.

  9. Coordination of Two On-Line Information Retrieval Services At the University of Minnesota Bio-Medical Library.

    Science.gov (United States)

    Egeland, Jan; Foreman, Gertrude

    The Bio-Medical Library at the University of Minnesota has access to two on-line computer systems: the MEDLINE system (MEDLARS ON-LINE) of the National Library of Medicine and the State University of New York (SUNY) Biomedical Communication Network. MEDLINE consists of two files which provide coverage of the "Index Medicus" from 1970 to the…

  10. Study of query expansion techniques and their application in the biomedical information retrieval.

    Science.gov (United States)

    Rivas, A R; Iglesias, E L; Borrajo, L

    2014-01-01

    Information Retrieval focuses on finding documents whose content matches with a user query from a large document collection. As formulating well-designed queries is difficult for most users, it is necessary to use query expansion to retrieve relevant information. Query expansion techniques are widely applied for improving the efficiency of the textual information retrieval systems. These techniques help to overcome vocabulary mismatch issues by expanding the original query with additional relevant terms and reweighting the terms in the expanded query. In this paper, different text preprocessing and query expansion approaches are combined to improve the documents initially retrieved by a query in a scientific documental database. A corpus belonging to MEDLINE, called Cystic Fibrosis, is used as a knowledge source. Experimental results show that the proposed combinations of techniques greatly enhance the efficiency obtained by traditional queries.

  11. Why not just Google it? An assessment of information literacy skills in a biomedical science curriculum

    Science.gov (United States)

    2011-01-01

    Background Few issues in higher education are as fundamental as the ability to search for, evaluate, and synthesize information. The need to develop information literacy, the process of finding, retrieving, organizing, and evaluating the ever-expanding collection of online information, has precipitated the need for training in skill-based competencies in higher education, as well as medical and dental education. Methods The current study evaluated the information literacy skills of first-year dental students, consisting of two, consecutive dental student cohorts (n = 160). An assignment designed to evaluate information literacy skills was conducted. In addition, a survey of student online search engine or database preferences was conducted to identify any significant associations. Subsequently, an intervention was developed, based upon the results of the assessment and survey, to address any deficiencies in information literacy. Results Nearly half of students (n = 70/160 or 43%) missed one or more question components that required finding an evidence-based citation. Analysis of the survey revealed a significantly higher percentage of students who provided incorrect responses (n = 53/70 or 75.7%) reported using Google as their preferred online search method (p < 0.01). In contrast, a significantly higher percentage of students who reported using PubMed (n = 39/45 or 86.7%) were able to provide correct responses (p < 0.01). Following a one-hour intervention by a health science librarian, virtually all students were able to find and retrieve evidence-based materials for subsequent coursework. Conclusions This study confirmed that information literacy among this student population was lacking and that integration of modules within the curriculum can help students to filter and establish the quality of online information, a critical component in the training of new health care professionals. Furthermore, incorporation of these modules early in the curriculum may be of

  12. Biomedical image representation approach using visualness and spatial information in a concept feature space for interactive region-of-interest-based retrieval.

    Science.gov (United States)

    Rahman, Md Mahmudur; Antani, Sameer K; Demner-Fushman, Dina; Thoma, George R

    2015-10-01

    This article presents an approach to biomedical image retrieval by mapping image regions to local concepts where images are represented in a weighted entropy-based concept feature space. The term "concept" refers to perceptually distinguishable visual patches that are identified locally in image regions and can be mapped to a glossary of imaging terms. Further, the visual significance (e.g., visualness) of concepts is measured as the Shannon entropy of pixel values in image patches and is used to refine the feature vector. Moreover, the system can assist the user in interactively selecting a region-of-interest (ROI) and searching for similar image ROIs. Further, a spatial verification step is used as a postprocessing step to improve retrieval results based on location information. The hypothesis that such approaches would improve biomedical image retrieval is validated through experiments on two different data sets, which are collected from open access biomedical literature.

  13. Advanced applications of natural language processing for performing information extraction

    CERN Document Server

    Rodrigues, Mário

    2015-01-01

    This book explains how can be created information extraction (IE) applications that are able to tap the vast amount of relevant information available in natural language sources: Internet pages, official documents such as laws and regulations, books and newspapers, and social web. Readers are introduced to the problem of IE and its current challenges and limitations, supported with examples. The book discusses the need to fill the gap between documents, data, and people, and provides a broad overview of the technology supporting IE. The authors present a generic architecture for developing systems that are able to learn how to extract relevant information from natural language documents, and illustrate how to implement working systems using state-of-the-art and freely available software tools. The book also discusses concrete applications illustrating IE uses.   ·         Provides an overview of state-of-the-art technology in information extraction (IE), discussing achievements and limitations for t...

  14. Information extraction from the GER 63-channel spectrometer data

    Science.gov (United States)

    Kiang, Richard K.

    1993-09-01

    The unprecedented data volume in the era of NASA's Mission to Planet Earth (MTPE) demands innovative information extraction methods and advanced processing techniques. The neural network techniques, which are intrinsic to distributed parallel processings and have shown promising results in analyzing remotely sensed data, could become the essential tools in the MTPE era. To evaluate the information content of data with higher dimension and the usefulness of neural networks in analyzing them, measurements from the GER 63-channel airborne imaging spectrometer data over Cuprite, Nevada, are used. The data are classified with 3-layer Perceptron of various architectures. It is shown that the neural network can achieve a level of performance similar to conventional methods, without the need for an explicit feature extraction step.

  15. Ethics Review Committee approval and informed consent: an analysis of biomedical publications originating from Sri Lanka

    Directory of Open Access Journals (Sweden)

    Siriwardhana Chesmal

    2008-02-01

    Full Text Available Abstract Background International guidelines on research have focused on protecting research participants. Ethical Research Committee (ERC approval and informed consent are the cornerstones. Externally sponsored research requires approval through ethical review in both the host and the sponsoring country. This study aimed to determine to what extent ERC approval and informed consent procedures are documented in locally and internationally published human subject research carried out in Sri Lanka. Methods We obtained ERC approval in Sri Lanka and the United Kingdom. Theses from 1985 to 2005 available at the Postgraduate Institute of Medicine (PGIM library affiliated to the University of Colombo were scrutinised using checklists agreed in consultation with senior research collaborators. A Medline search was carried out with MeSH major and minor heading 'Sri Lanka' as the search term for international publications originating in Sri Lanka during 1999 to 2004. All research publications from CMJ during 1999 to 2005 were also scrutinized. Results Of 291 theses, 34% documented ERC approvals and 61% documented obtaining consent. From the international journal survey, 250 publications originated from Sri Lanka of which only 79 full text original research publications could be accessed electronically. Of these 38% documented ERC approval and 39% documented obtaining consent. In the Ceylon Medical Journal 36% documented ERC approval and 37% documented obtaining consent. Conclusion Only one third of the publications scrutinized recorded ERC approval and procurement of informed consent. However, there is a positive trend in documenting these ethical requirements in local postgraduate research and in the local medical journal.

  16. A new method for precursory information extraction: Slope-difference information method

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    A new method for precursory information extraction, i.e.,slope-difference information method is proposed in the paper for the daily-mean-value precursory data sequence. Taking Tangshan station as an example, the calculation of full-time-domain leveling data is made, which is tested and compared with several other methods. The results indicate that the method is very effective for extracting short-term precursory information from the daily mean values after the optimization is made. Therefore, it is valuable for popularization and application.

  17. Extracting Firm Information from Administrative Records: The ASSD Firm Panel

    OpenAIRE

    Fink, Martina; Segalla, Esther; Weber, Andrea; Zulehner, Christine

    2010-01-01

    This paper demonstrates how firm information can be extracted from administrative social security records. We use the Austrian Social Security Database (ASSD) and derive firms from employer identifiers in the universe of private sector workers. To correctly pin down entry end exits we use a worker flow approach which follows clusters of workers as they move across administrative entities. This procedure enables us to define different types of entry and exit such as start-ups, spinoffs, closur...

  18. A Semantic Approach for Geospatial Information Extraction from Unstructured Documents

    Science.gov (United States)

    Sallaberry, Christian; Gaio, Mauro; Lesbegueries, Julien; Loustau, Pierre

    Local cultural heritage document collections are characterized by their content, which is strongly attached to a territory and its land history (i.e., geographical references). Our contribution aims at making the content retrieval process more efficient whenever a query includes geographic criteria. We propose a core model for a formal representation of geographic information. It takes into account characteristics of different modes of expression, such as written language, captures of drawings, maps, photographs, etc. We have developed a prototype that fully implements geographic information extraction (IE) and geographic information retrieval (IR) processes. All PIV prototype processing resources are designed as Web Services. We propose a geographic IE process based on semantic treatment as a supplement to classical IE approaches. We implement geographic IR by using intersection computing algorithms that seek out any intersection between formal geocoded representations of geographic information in a user query and similar representations in document collection indexes.

  19. Extraction of hidden information by efficient community detection in networks

    CERN Document Server

    Lee, Juyong; Lee, Jooyoung

    2012-01-01

    Currently, we are overwhelmed by a deluge of experimental data, and network physics has the potential to become an invaluable method to increase our understanding of large interacting datasets. However, this potential is often unrealized for two reasons: uncovering the hidden community structure of a network, known as community detection, is difficult, and further, even if one has an idea of this community structure, it is not a priori obvious how to efficiently use this information. Here, to address both of these issues, we, first, identify optimal community structure of given networks in terms of modularity by utilizing a recently introduced community detection method. Second, we develop an approach to use this community information to extract hidden information from a network. When applied to a protein-protein interaction network, the proposed method outperforms current state-of-the-art methods that use only the local information of a network. The method is generally applicable to networks from many areas.

  20. Mutual information theory for biomedical applications: Estimation of three protein-adsorbed dialysis membranes

    Science.gov (United States)

    Aoyagi, Satoka; Takesawa, Azusa; Yamashita, Akihiro C.; Kudo, Masahiro

    2006-07-01

    Protein-adsorbed dialysis membranes are evaluated with time-of-flight secondary ion mass spectrometry (TOF-SIMS) chemical imaging technique. Protein adsorption causing permeability change is one of big issues in the development of dialysis membranes. Bovine serum albumin adsorption onto three kinds of dialysis membranes has been evaluated with TOF-SIMS. In the present study three kinds of proteins, bovine serum albumin, α-chymotripsinogen A, and cytochrome C adsorbed onto hollow-fiber dialysis membranes, were measured by means of TOF-SIMS and then TOF-SIMS spectra were analyzed using mutual information. Then specific peaks of fragment ions related to α-chymotripsinogen A and bovine serum albumin were found, respectively. In this condition, however, specific peaks to cytochrome C were not able to find compared with other samples. Finally, chemical images of α-chymotripsinogen A and bovine serum albumin, respectively, adsorbed onto the membranes with co-existing proteins were obtained. The results of TOF-SIMS images of the proteins on the membranes show different tendency of adsorption depending on co-existing proteins. Further study is needed to study more detailed protein adsorption onto the membranes with co-existing proteins.

  1. Extraction of spatial information for low-bandwidth telerehabilitation applications

    Directory of Open Access Journals (Sweden)

    Kok Kiong Tan, PhD

    2014-09-01

    Full Text Available Telemedicine applications, based on two-dimensional (2D video conferencing technology, have been around for the past 15 to 20 yr. They have been demonstrated to be acceptable for face-to-face consultations and useful for visual examination of wounds and abrasions. However, certain telerehabilitation assessments need the use of spatial information in order to accurately assess the patient’s condition and sending three-dimensional video data over low-bandwidth networks is extremely challenging. This article proposes an innovative way of extracting the key spatial information from the patient’s movement during telerehabilitation assessment based on 2D video and then presenting the extracted data by using graph plots alongside the video to help physicians in assessments with minimum burden on existing video data transfer. Some common rehabilitation scenarios are chosen for illustrations, and experiments are conducted based on skeletal tracking and color detection algorithms using the Microsoft Kinect sensor. Extracted data are analyzed in detail and their usability discussed.

  2. Transliteration normalization for Information Extraction and Machine Translation

    Directory of Open Access Journals (Sweden)

    Yuval Marton

    2014-12-01

    Full Text Available Foreign name transliterations typically include multiple spelling variants. These variants cause data sparseness and inconsistency problems, increase the Out-of-Vocabulary (OOV rate, and present challenges for Machine Translation, Information Extraction and other natural language processing (NLP tasks. This work aims to identify and cluster name spelling variants using a Statistical Machine Translation method: word alignment. The variants are identified by being aligned to the same “pivot” name in another language (the source-language in Machine Translation settings. Based on word-to-word translation and transliteration probabilities, as well as the string edit distance metric, names with similar spellings in the target language are clustered and then normalized to a canonical form. With this approach, tens of thousands of high-precision name transliteration spelling variants are extracted from sentence-aligned bilingual corpora in Arabic and English (in both languages. When these normalized name spelling variants are applied to Information Extraction tasks, improvements over strong baseline systems are observed. When applied to Machine Translation tasks, a large improvement potential is shown.

  3. THE METHODS OF EXTRACTING WATER INFORMATION FROM SPOT IMAGE

    Institute of Scientific and Technical Information of China (English)

    DUJin-kang; FENGXue-zhi; 等

    2002-01-01

    Some techniques and methods for deriving water information from SPOT-4(XI) image were investigated and discussed in this paper.An algorithmoif decision-tree(DT) classification which includes several classifiers based on the spectral responding characteristics of water bodies and other objects,was developed and put forward to delineate water bodies.Another algorithm of decision-tree classification based on both spectral characteristics and auxiliary information of DEM and slope(DTDS) was also designed for water bodies extraction.In addition,supervised classification method of maximum-likelyhood classification(MLC),and unsupervised method of interactive self -organizing dada analysis technique(ISODATA) were used to extract waterbodies for comparison purpose.An index was designed and used to assess the accuracy of different methods abopted in the research.Results have shown that water extraction accuracy was variable with respect to the various techniques applied.It was low using ISODATA,very high using DT algorithm and much higher using both DTDS and MLC.

  4. [Study on Information Extraction of Clinic Expert Information from Hospital Portals].

    Science.gov (United States)

    Zhang, Yuanpeng; Dong, Jiancheng; Qian, Danmin; Geng, Xingyun; Wu, Huiqun; Wang, Li

    2015-12-01

    Clinic expert information provides important references for residents in need of hospital care. Usually, such information is hidden in the deep web and cannot be directly indexed by search engines. To extract clinic expert information from the deep web, the first challenge is to make a judgment on forms. This paper proposes a novel method based on a domain model, which is a tree structure constructed by the attributes of search interfaces. With this model, search interfaces can be classified to a domain and filled in with domain keywords. Another challenge is to extract information from the returned web pages indexed by search interfaces. To filter the noise information on a web page, a block importance model is proposed. The experiment results indicated that the domain model yielded a precision 10.83% higher than that of the rule-based method, whereas the block importance model yielded an F₁ measure 10.5% higher than that of the XPath method.

  5. Knowledge discovery: Extracting usable information from large amounts of data

    Energy Technology Data Exchange (ETDEWEB)

    Whiteson, R.

    1998-12-31

    The threat of nuclear weapons proliferation is a problem of world wide concern. Safeguards are the key to nuclear nonproliferation and data is the key to safeguards. The safeguards community has access to a huge and steadily growing volume of data. The advantages of this data rich environment are obvious, there is a great deal of information which can be utilized. The challenge is to effectively apply proven and developing technologies to find and extract usable information from that data. That information must then be assessed and evaluated to produce the knowledge needed for crucial decision making. Efficient and effective analysis of safeguards data will depend on utilizing technologies to interpret the large, heterogeneous data sets that are available from diverse sources. With an order-of-magnitude increase in the amount of data from a wide variety of technical, textual, and historical sources there is a vital need to apply advanced computer technologies to support all-source analysis. There are techniques of data warehousing, data mining, and data analysis that can provide analysts with tools that will expedite their extracting useable information from the huge amounts of data to which they have access. Computerized tools can aid analysts by integrating heterogeneous data, evaluating diverse data streams, automating retrieval of database information, prioritizing inputs, reconciling conflicting data, doing preliminary interpretations, discovering patterns or trends in data, and automating some of the simpler prescreening tasks that are time consuming and tedious. Thus knowledge discovery technologies can provide a foundation of support for the analyst. Rather than spending time sifting through often irrelevant information, analysts could use their specialized skills in a focused, productive fashion. This would allow them to make their analytical judgments with more confidence and spend more of their time doing what they do best.

  6. Extraction of Coupling Information From $Z' \\to jj$

    CERN Document Server

    Rizzo, T G

    1993-01-01

    An analysis by the ATLAS Collaboration has recently shown, contrary to popular belief, that a combination of strategic cuts, excellent mass resolution, and detailed knowledge of the QCD backgrounds from direct measurements can be used to extract a signal in the $Z' \\to jj$ channel in excess of $6\\sigma$ for certain classes of extended electroweak models. We explore the possibility that the data extracted from $Z$ dijet peak will have sufficient statistical power as to supply information on the couplings of the $Z'$ provided it is used in conjunction with complimentary results from the $Z' \\to \\ell^+ \\ell^-$ `discovery' channel. We show, for a 1 TeV $Z'$ produced at the SSC, that this technique can provide a powerful new tool with which to identify the origin of $Z'$'s.

  7. Extraction of coupling information from Z'-->jj

    Science.gov (United States)

    Rizzo, Thomas G.

    1993-11-01

    An analysis by the ATLAS Collaboration has recently shown, contrary to popular belief, that a combination of strategic cuts, excellent mass resolution, and detailed knowledge of the QCD backgrounds from direct measurements can be used to extract a signal in the Z'-->jj channel for certain classes of extended electroweak models. We explore the possibility that the data extracted from Z dijet peak will have sufficient statistical power as to supply information on the couplings of the Z' provided it is used in conjunction with complementary results from the Z'-->l+l- ``discovery'' channel. We show, for a 1 TeV Z' produced at the SSC, that this technique can provide a powerful new tool with which to identify the origin of Z'. Extensions of this analysis to the CERN LHC as well as for a more massive Z' are discussed.

  8. Audio enabled information extraction system for cricket and hockey domains

    CERN Document Server

    Saraswathi, S; B., Sai Vamsi Krishna; S, Suresh Reddy

    2010-01-01

    The proposed system aims at the retrieval of the summarized information from the documents collected from web based search engine as per the user query related to cricket and hockey domain. The system is designed in a manner that it takes the voice commands as keywords for search. The parts of speech in the query are extracted using the natural language extractor for English. Based on the keywords the search is categorized into 2 types: - 1.Concept wise - information retrieved to the query is retrieved based on the keywords and the concept words related to it. The retrieved information is summarized using the probabilistic approach and weighted means algorithm.2.Keyword search - extracts the result relevant to the query from the highly ranked document retrieved from the search by the search engine. The relevant search results are retrieved and then keywords are used for summarizing part. During summarization it follows the weighted and probabilistic approaches in order to identify the data comparable to the k...

  9. ONTOGRABBING: Extracting Information from Texts Using Generative Ontologies

    DEFF Research Database (Denmark)

    Nilsson, Jørgen Fischer; Szymczak, Bartlomiej Antoni; Jensen, P.A.

    2009-01-01

    We describe principles for extracting information from texts using a so-called generative ontology in combination with syntactic analysis. Generative ontologies are introduced as semantic domains for natural language phrases. Generative ontologies extend ordinary finite ontologies with rules...... for producing recursively shaped terms representing the ontological content (ontological semantics) of NL noun phrases and other phrases. We focus here on achieving a robust, often only partial, ontology-driven parsing of and ascription of semantics to a sentence in the text corpus. The aim of the ontological...

  10. A High Accuracy Method for Semi-supervised Information Extraction

    Energy Technology Data Exchange (ETDEWEB)

    Tratz, Stephen C.; Sanfilippo, Antonio P.

    2007-04-22

    Customization to specific domains of dis-course and/or user requirements is one of the greatest challenges for today’s Information Extraction (IE) systems. While demonstrably effective, both rule-based and supervised machine learning approaches to IE customization pose too high a burden on the user. Semi-supervised learning approaches may in principle offer a more resource effective solution but are still insufficiently accurate to grant realistic application. We demonstrate that this limitation can be overcome by integrating fully-supervised learning techniques within a semi-supervised IE approach, without increasing resource requirements.

  11. Using XBRL Technology to Extract Competitive Information from Financial Statements

    Directory of Open Access Journals (Sweden)

    Dominik Ditter

    2011-12-01

    Full Text Available The eXtensible Business Reporting Language, or XBRL, is a reporting format for the automatic and electronic exchange of business and financial data. In XBRL every single reported fact is marked with a unique tag, enabling a full computer-based readout of financial data. It has the potential to improve the collection and analysis of financial data for Competitive Intelligence (e.g., the profiling of publicly available financial statements. The article describes how easily information from XBRL reports can be extracted.

  12. Automated extraction of chemical structure information from digital raster images

    Directory of Open Access Journals (Sweden)

    Shedden Kerby A

    2009-02-01

    Full Text Available Abstract Background To search for chemical structures in research articles, diagrams or text representing molecules need to be translated to a standard chemical file format compatible with cheminformatic search engines. Nevertheless, chemical information contained in research articles is often referenced as analog diagrams of chemical structures embedded in digital raster images. To automate analog-to-digital conversion of chemical structure diagrams in scientific research articles, several software systems have been developed. But their algorithmic performance and utility in cheminformatic research have not been investigated. Results This paper aims to provide critical reviews for these systems and also report our recent development of ChemReader – a fully automated tool for extracting chemical structure diagrams in research articles and converting them into standard, searchable chemical file formats. Basic algorithms for recognizing lines and letters representing bonds and atoms in chemical structure diagrams can be independently run in sequence from a graphical user interface-and the algorithm parameters can be readily changed-to facilitate additional development specifically tailored to a chemical database annotation scheme. Compared with existing software programs such as OSRA, Kekule, and CLiDE, our results indicate that ChemReader outperforms other software systems on several sets of sample images from diverse sources in terms of the rate of correct outputs and the accuracy on extracting molecular substructure patterns. Conclusion The availability of ChemReader as a cheminformatic tool for extracting chemical structure information from digital raster images allows research and development groups to enrich their chemical structure databases by annotating the entries with published research articles. Based on its stable performance and high accuracy, ChemReader may be sufficiently accurate for annotating the chemical database with links

  13. Karst rocky desertification information extraction with EO-1 Hyperion data

    Science.gov (United States)

    Yue, Yuemin; Wang, Kelin; Zhang, Bing; Jiao, Quanjun; Yu, Yizun

    2008-12-01

    Karst rocky desertification is a special kind of land desertification developed under violent human impacts on the vulnerable eco-geo-environment of karst ecosystem. The process of karst rocky desertification results in simultaneous and complex variations of many interrelated soil, rock and vegetation biogeophysical parameters, rendering it difficult to develop simple and robust remote sensing mapping and monitoring approaches. In this study, we aimed to use Earth Observing 1 (EO-1) Hyperion hyperspectral data to extract the karst rocky desertification information. A spectral unmixing model based on Monte Carlo approach, was employed to quantify the fractional cover of photosynthetic vegetation (PV), non-photosynthetic vegetation (NPV) and bare substrates. The results showed that SWIR (1.9-2.35μm) portions of the spectrum were significantly different in PV, NPV and bare rock spectral properties. It has limitations in using full optical range or only SWIR (1.9-2.35μm) region of Hyperion to decompose image into PV, NPV and bare substrates covers. However, when use the tied-SWIR, the sub-pixel fractional covers of PV, NPV and bare substrates were accurately estimated. Our study indicates that the "tied-spectrum" method effectively accentuate the spectral characteristics of materials, while the spectral unmixing model based on Monte Carlo approach is a useful tool to automatically extract mixed ground objects in karst ecosystem. Karst rocky desertification information can be accurately extracted with EO-1 Hyperion. Imaging spectroscopy can provide a powerful methodology toward understanding the extent and spatial pattern of land degradation in karst ecosystem.

  14. Extraction of hidden information by efficient community detection in networks

    Science.gov (United States)

    Lee, Jooyoung; Lee, Juyong; Gross, Steven

    2013-03-01

    Currently, we are overwhelmed by a deluge of experimental data, and network physics has the potential to become an invaluable method to increase our understanding of large interacting datasets. However, this potential is often unrealized for two reasons: uncovering the hidden community structure of a network, known as community detection, is difficult, and further, even if one has an idea of this community structure, it is not a priori obvious how to efficiently use this information. Here, to address both of these issues, we, first, identify optimal community structure of given networks in terms of modularity by utilizing a recently introduced community detection method. Second, we develop an approach to use this community information to extract hidden information from a network. When applied to a protein-protein interaction network, the proposed method outperforms current state-of-the-art methods that use only the local information of a network. The method is generally applicable to networks from many areas. This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MEST) (No. 20120001222).

  15. What is biomedical informatics?

    Science.gov (United States)

    Bernstam, Elmer V; Smith, Jack W; Johnson, Todd R

    2010-02-01

    Biomedical informatics lacks a clear and theoretically-grounded definition. Many proposed definitions focus on data, information, and knowledge, but do not provide an adequate definition of these terms. Leveraging insights from the philosophy of information, we define informatics as the science of information, where information is data plus meaning. Biomedical informatics is the science of information as applied to or studied in the context of biomedicine. Defining the object of study of informatics as data plus meaning clearly distinguishes the field from related fields, such as computer science, statistics and biomedicine, which have different objects of study. The emphasis on data plus meaning also suggests that biomedical informatics problems tend to be difficult when they deal with concepts that are hard to capture using formal, computational definitions. In other words, problems where meaning must be considered are more difficult than problems where manipulating data without regard for meaning is sufficient. Furthermore, the definition implies that informatics research, teaching, and service should focus on biomedical information as data plus meaning rather than only computer applications in biomedicine.

  16. Biomedical photonics handbook biomedical diagnostics

    CERN Document Server

    Vo-Dinh, Tuan

    2014-01-01

    Shaped by Quantum Theory, Technology, and the Genomics RevolutionThe integration of photonics, electronics, biomaterials, and nanotechnology holds great promise for the future of medicine. This topic has recently experienced an explosive growth due to the noninvasive or minimally invasive nature and the cost-effectiveness of photonic modalities in medical diagnostics and therapy. The second edition of the Biomedical Photonics Handbook presents fundamental developments as well as important applications of biomedical photonics of interest to scientists, engineers, manufacturers, teachers, studen

  17. Research of information classification and strategy intelligence extract algorithm based on military strategy hall

    Science.gov (United States)

    Chen, Lei; Li, Dehua; Yang, Jie

    2007-12-01

    Constructing virtual international strategy environment needs many kinds of information, such as economy, politic, military, diploma, culture, science, etc. So it is very important to build an information auto-extract, classification, recombination and analysis management system with high efficiency as the foundation and component of military strategy hall. This paper firstly use improved Boost algorithm to classify obtained initial information, then use a strategy intelligence extract algorithm to extract strategy intelligence from initial information to help strategist to analysis information.

  18. Querying and Extracting Timeline Information from Road Traffic Sensor Data.

    Science.gov (United States)

    Imawan, Ardi; Indikawati, Fitri Indra; Kwon, Joonho; Rao, Praveen

    2016-08-23

    The escalation of traffic congestion in urban cities has urged many countries to use intelligent transportation system (ITS) centers to collect historical traffic sensor data from multiple heterogeneous sources. By analyzing historical traffic data, we can obtain valuable insights into traffic behavior. Many existing applications have been proposed with limited analysis results because of the inability to cope with several types of analytical queries. In this paper, we propose the QET (querying and extracting timeline information) system-a novel analytical query processing method based on a timeline model for road traffic sensor data. To address query performance, we build a TQ-index (timeline query-index) that exploits spatio-temporal features of timeline modeling. We also propose an intuitive timeline visualization method to display congestion events obtained from specified query parameters. In addition, we demonstrate the benefit of our system through a performance evaluation using a Busan ITS dataset and a Seattle freeway dataset.

  19. Domain-independent information extraction in unstructured text

    Energy Technology Data Exchange (ETDEWEB)

    Irwin, N.H. [Sandia National Labs., Albuquerque, NM (United States). Software Surety Dept.

    1996-09-01

    Extracting information from unstructured text has become an important research area in recent years due to the large amount of text now electronically available. This status report describes the findings and work done during the second year of a two-year Laboratory Directed Research and Development Project. Building on the first-year`s work of identifying important entities, this report details techniques used to group words into semantic categories and to output templates containing selective document content. Using word profiles and category clustering derived during a training run, the time-consuming knowledge-building task can be avoided. Though the output still lacks in completeness when compared to systems with domain-specific knowledge bases, the results do look promising. The two approaches are compatible and could complement each other within the same system. Domain-independent approaches retain appeal as a system that adapts and learns will soon outpace a system with any amount of a priori knowledge.

  20. A nonparametric approach to extract information from interspike interval data.

    Science.gov (United States)

    Rossoni, Enrico; Feng, Jianfeng

    2006-01-15

    In this work we develop an approach to extracting information from neural spike trains. Using the expectation-maximization (EM) algorithm, interspike interval data from experiments and simulations are fitted by mixtures of distributions, including Gamma, inverse Gaussian, log-normal, and the distribution of the interspike intervals of the leaky integrate-and-fire model. In terms of the Kolmogorov-Smirnov test for goodness-of-fit, our approach is proved successful (P>0.05) in fitting benchmark data for which a classical parametric approach has been shown to fail before. In addition, we present a novel method to fit mixture models to censored data, and discuss two examples of the application of such a method, which correspond to the case of multiple-trial and multielectrode array data. A MATLAB implementation of the algorithm is available for download from .

  1. Querying and Extracting Timeline Information from Road Traffic Sensor Data

    Directory of Open Access Journals (Sweden)

    Ardi Imawan

    2016-08-01

    Full Text Available The escalation of traffic congestion in urban cities has urged many countries to use intelligent transportation system (ITS centers to collect historical traffic sensor data from multiple heterogeneous sources. By analyzing historical traffic data, we can obtain valuable insights into traffic behavior. Many existing applications have been proposed with limited analysis results because of the inability to cope with several types of analytical queries. In this paper, we propose the QET (querying and extracting timeline information system—a novel analytical query processing method based on a timeline model for road traffic sensor data. To address query performance, we build a TQ-index (timeline query-index that exploits spatio-temporal features of timeline modeling. We also propose an intuitive timeline visualization method to display congestion events obtained from specified query parameters. In addition, we demonstrate the benefit of our system through a performance evaluation using a Busan ITS dataset and a Seattle freeway dataset.

  2. Ranking Biomedical Annotations with Annotator’s Semantic Relevancy

    Directory of Open Access Journals (Sweden)

    Aihua Wu

    2014-01-01

    Full Text Available Biomedical annotation is a common and affective artifact for researchers to discuss, show opinion, and share discoveries. It becomes increasing popular in many online research communities, and implies much useful information. Ranking biomedical annotations is a critical problem for data user to efficiently get information. As the annotator’s knowledge about the annotated entity normally determines quality of the annotations, we evaluate the knowledge, that is, semantic relationship between them, in two ways. The first is extracting relational information from credible websites by mining association rules between an annotator and a biomedical entity. The second way is frequent pattern mining from historical annotations, which reveals common features of biomedical entities that an annotator can annotate with high quality. We propose a weighted and concept-extended RDF model to represent an annotator, a biomedical entity, and their background attributes and merge information from the two ways as the context of an annotator. Based on that, we present a method to rank the annotations by evaluating their correctness according to user’s vote and the semantic relevancy between the annotator and the annotated entity. The experimental results show that the approach is applicable and efficient even when data set is large.

  3. Biomedical nanotechnology.

    Science.gov (United States)

    Hurst, Sarah J

    2011-01-01

    This chapter summarizes the roles of nanomaterials in biomedical applications, focusing on those highlighted in this volume. A brief history of nanoscience and technology and a general introduction to the field are presented. Then, the chemical and physical properties of nanostructures that make them ideal for use in biomedical applications are highlighted. Examples of common applications, including sensing, imaging, and therapeutics, are given. Finally, the challenges associated with translating this field from the research laboratory to the clinic setting, in terms of the larger societal implications, are discussed.

  4. miRSel: Automated extraction of associations between microRNAs and genes from the biomedical literature

    Directory of Open Access Journals (Sweden)

    Zimmer Ralf

    2010-03-01

    Full Text Available Abstract Background MicroRNAs have been discovered as important regulators of gene expression. To identify the target genes of microRNAs, several databases and prediction algorithms have been developed. Only few experimentally confirmed microRNA targets are available in databases. Many of the microRNA targets stored in databases were derived from large-scale experiments that are considered not very reliable. We propose to use text mining of publication abstracts for extracting microRNA-gene associations including microRNA-target relations to complement current repositories. Results The microRNA-gene association database miRSel combines text-mining results with existing databases and computational predictions. Text mining enables the reliable extraction of microRNA, gene and protein occurrences as well as their relationships from texts. Thereby, we increased the number of human, mouse and rat miRNA-gene associations by at least three-fold as compared to e.g. TarBase, a resource for miRNA-gene associations. Conclusions Our database miRSel offers the currently largest collection of literature derived miRNA-gene associations. Comprehensive collections of miRNA-gene associations are important for the development of miRNA target prediction tools and the analysis of regulatory networks. miRSel is updated daily and can be queried using a web-based interface via microRNA identifiers, gene and protein names, PubMed queries as well as gene ontology (GO terms. miRSel is freely available online at http://services.bio.ifi.lmu.de/mirsel.

  5. Biomedical Engineering

    CERN Document Server

    Suh, Sang C; Tanik, Murat M

    2011-01-01

    Biomedical Engineering: Health Care Systems, Technology and Techniques is an edited volume with contributions from world experts. It provides readers with unique contributions related to current research and future healthcare systems. Practitioners and researchers focused on computer science, bioinformatics, engineering and medicine will find this book a valuable reference.

  6. Biomedical Libraries

    Science.gov (United States)

    Pizer, Irwin H.

    1978-01-01

    Biomedical libraries are discussed as a distinct and specialized group of special libraries and their unique services and user interactions are described. The move toward professional standards, as evidenced by the Medical Library Association's new certification program, and the current state of development for a new section of IFLA established…

  7. Extracting information in spike time patterns with wavelets and information theory.

    Science.gov (United States)

    Lopes-dos-Santos, Vítor; Panzeri, Stefano; Kayser, Christoph; Diamond, Mathew E; Quian Quiroga, Rodrigo

    2015-02-01

    We present a new method to assess the information carried by temporal patterns in spike trains. The method first performs a wavelet decomposition of the spike trains, then uses Shannon information to select a subset of coefficients carrying information, and finally assesses timing information in terms of decoding performance: the ability to identify the presented stimuli from spike train patterns. We show that the method allows: 1) a robust assessment of the information carried by spike time patterns even when this is distributed across multiple time scales and time points; 2) an effective denoising of the raster plots that improves the estimate of stimulus tuning of spike trains; and 3) an assessment of the information carried by temporally coordinated spikes across neurons. Using simulated data, we demonstrate that the Wavelet-Information (WI) method performs better and is more robust to spike time-jitter, background noise, and sample size than well-established approaches, such as principal component analysis, direct estimates of information from digitized spike trains, or a metric-based method. Furthermore, when applied to real spike trains from monkey auditory cortex and from rat barrel cortex, the WI method allows extracting larger amounts of spike timing information. Importantly, the fact that the WI method incorporates multiple time scales makes it robust to the choice of partly arbitrary parameters such as temporal resolution, response window length, number of response features considered, and the number of available trials. These results highlight the potential of the proposed method for accurate and objective assessments of how spike timing encodes information.

  8. Earth Science Data Analytics: Preparing for Extracting Knowledge from Information

    Science.gov (United States)

    Kempler, Steven; Barbieri, Lindsay

    2016-01-01

    Data analytics is the process of examining large amounts of data of a variety of types to uncover hidden patterns, unknown correlations and other useful information. Data analytics is a broad term that includes data analysis, as well as an understanding of the cognitive processes an analyst uses to understand problems and explore data in meaningful ways. Analytics also include data extraction, transformation, and reduction, utilizing specific tools, techniques, and methods. Turning to data science, definitions of data science sound very similar to those of data analytics (which leads to a lot of the confusion between the two). But the skills needed for both, co-analyzing large amounts of heterogeneous data, understanding and utilizing relevant tools and techniques, and subject matter expertise, although similar, serve different purposes. Data Analytics takes on a practitioners approach to applying expertise and skills to solve issues and gain subject knowledge. Data Science, is more theoretical (research in itself) in nature, providing strategic actionable insights and new innovative methodologies. Earth Science Data Analytics (ESDA) is the process of examining, preparing, reducing, and analyzing large amounts of spatial (multi-dimensional), temporal, or spectral data using a variety of data types to uncover patterns, correlations and other information, to better understand our Earth. The large variety of datasets (temporal spatial differences, data types, formats, etc.) invite the need for data analytics skills that understand the science domain, and data preparation, reduction, and analysis techniques, from a practitioners point of view. The application of these skills to ESDA is the focus of this presentation. The Earth Science Information Partners (ESIP) Federation Earth Science Data Analytics (ESDA) Cluster was created in recognition of the practical need to facilitate the co-analysis of large amounts of data and information for Earth science. Thus, from a to

  9. [The Internet and clinical medicine. An introduction to the biomedical information services available in electronic form on the "net of all nets"].

    Science.gov (United States)

    Tringali, M; Iannucci, P; Zani, M

    1996-05-01

    Clinical users expectations from medical informatics are evolving due to the wide availability of biomedical information services on the Internet. Thanks to hypertexts and advanced browsing tools users with no informatical expertise can travel on the Internet and easily gain access to textual databases. With a multimedia computer other kinds of information can be grabbed: images, sounds and audiovisual documents. Basic Internet services (electronic mail, discussion lists, file transfer protocol, terminal emulation) can be accessed from a wide range of hardware equipment. However, the real power of a world-scale computer network like the Internet will be unleashed only when its global connectivity will be linked to the powerful retrieval ability of existing clinical and related databases. While biomedical journals editors and other medical information providers are in the way to offer electronic versions of their paper-based products, at the leading edge of this world-scale process is the USA National Library of Medicine, with the Internet-compatible version of its Grateful Med software which is expected to be launched during 1996.

  10. [Evidence-based medicine. 2. Research of clinically relevant biomedical information. Gruppo Italiano per la Medicina Basata sulle Evidenze--GIMBE].

    Science.gov (United States)

    Cartabellotta, A

    1998-05-01

    Evidence-based Medicine is a product of the electronic information age and there are several databases useful for practice it--MEDLINE, EMBASE, specialized compendiums of evidence (Cochrane Library, Best Evidence), practice guidelines--most of them free available through Internet, that offers a growing number of health resources. Because searching best evidence is a basic step to practice Evidence-based Medicine, this second review (the first one has been published in the issue of March 1998) has the aim to provide physicians tools and skills for retrieving relevant biomedical information. Therefore, we discuss about strategies for managing information overload, analyze characteristics, usefulness and limits of medical databases and explain how to use MEDLINE in day-to-day clinical practice.

  11. Biomedical Materials

    Institute of Scientific and Technical Information of China (English)

    CHANG Jiang; ZHOU Yanling

    2011-01-01

    @@ Biomedical materials, biomaterials for short, is regarded as "any substance or combination of substances, synthetic or natural in origin, which can be used for any period of time, as a whole or as part of a system which treats, augments, or replaces any tissue, organ or function of the body" (Vonrecum & Laberge, 1995).Biomaterials can save lives, relieve suffering and enhance the quality of life for human being.

  12. Computational intelligence in biomedical imaging

    CERN Document Server

    2014-01-01

    This book provides a comprehensive overview of the state-of-the-art computational intelligence research and technologies in biomedical images with emphasis on biomedical decision making. Biomedical imaging offers useful information on patients’ medical conditions and clues to causes of their symptoms and diseases. Biomedical images, however, provide a large number of images which physicians must interpret. Therefore, computer aids are demanded and become indispensable in physicians’ decision making. This book discusses major technical advancements and research findings in the field of computational intelligence in biomedical imaging, for example, computational intelligence in computer-aided diagnosis for breast cancer, prostate cancer, and brain disease, in lung function analysis, and in radiation therapy. The book examines technologies and studies that have reached the practical level, and those technologies that are becoming available in clinical practices in hospitals rapidly such as computational inte...

  13. Text mining patents for biomedical knowledge.

    Science.gov (United States)

    Rodriguez-Esteban, Raul; Bundschus, Markus

    2016-06-01

    Biomedical text mining of scientific knowledge bases, such as Medline, has received much attention in recent years. Given that text mining is able to automatically extract biomedical facts that revolve around entities such as genes, proteins, and drugs, from unstructured text sources, it is seen as a major enabler to foster biomedical research and drug discovery. In contrast to the biomedical literature, research into the mining of biomedical patents has not reached the same level of maturity. Here, we review existing work and highlight the associated technical challenges that emerge from automatically extracting facts from patents. We conclude by outlining potential future directions in this domain that could help drive biomedical research and drug discovery.

  14. Medicaid Analytic eXtract (MAX) General Information

    Data.gov (United States)

    U.S. Department of Health & Human Services — The Medicaid Analytic eXtract (MAX) data is a set of person-level data files on Medicaid eligibility, service utilization, and payments. The MAX data are created to...

  15. Automatic Data Extraction from Websites for Generating Aquatic Product Market Information

    Institute of Scientific and Technical Information of China (English)

    YUAN Hong-chun; CHEN Ying; SUN Yue-fu

    2006-01-01

    The massive web-based information resources have led to an increasing demand for effective automatic retrieval of target information for web applications. This paper introduces a web-based data extraction tool that deploys various algorithms to locate, extract and filter tabular data from HTML pages and to transform them into new web-based representations. The tool has been applied in an aquaculture web application platform for extracting and generating aquatic product market information.Results prove that this tool is very effective in extracting the required data from web pages.

  16. Holography In Biomedical Sciences

    Science.gov (United States)

    von Bally, G.

    1988-01-01

    Today not only physicists and engineers but also biological and medical scientists are exploring the potentials of holographic methods in their special field of work. Most of the underlying physical principles such as coherence, interference, diffraction and polarization as well as general features of holography e.g. storage and retrieval of amplitude and phase of a wavefront, 3-d-imaging, large field of depth, redundant storage of information, spatial filtering, high-resolving, non-contactive, 3-d form and motion analysis are explained in detail in other contributions to this book. Therefore, this article is confined to the applications of holography in biomedical sciences. Because of the great number of contributions and the variety of applications [1,2,3,4,5,6,7,8] in this review the investigations can only be mentioned briefly and the survey has to be confined to some examples. As in all fields of optics and laser metrology, a review of biomedical applications of holography would be incomplete if military developments and their utilization are not mentioned. As will be demonstrated by selected examples the increasing interlacing of science with the military does not stop at domains that traditionally are regarded as exclusively oriented to human welfare like biomedical research [9]. This fact is actually characterized and stressed by the expression "Star Wars Medicine", which becomes increasingly common as popular description for laser applications (including holography) in medicine [10]. Thus, the consequence - even in such highly specialized fields like biomedical applications of holography - have to be discussed.

  17. Information Extraction, Data Integration, and Uncertain Data Management: The State of The Art

    NARCIS (Netherlands)

    Habib, Mena B.; Keulen, van Maurice

    2011-01-01

    Information Extraction, data Integration, and uncertain data management are different areas of research that got vast focus in the last two decades. Many researches tackled those areas of research individually. However, information extraction systems should have integrated with data integration meth

  18. Semantic Preview Benefit in English: Individual Differences in the Extraction and Use of Parafoveal Semantic Information

    Science.gov (United States)

    Veldre, Aaron; Andrews, Sally

    2016-01-01

    Although there is robust evidence that skilled readers of English extract and use orthographic and phonological information from the parafovea to facilitate word identification, semantic preview benefits have been elusive. We sought to establish whether individual differences in the extraction and/or use of parafoveal semantic information could…

  19. Towards an information extraction and knowledge formation framework based on Shannon entropy

    Directory of Open Access Journals (Sweden)

    Iliescu Dragoș

    2017-01-01

    Full Text Available Information quantity subject is approached in this paperwork, considering the specific domain of nonconforming product management as information source. This work represents a case study. Raw data were gathered from a heavy industrial works company, information extraction and knowledge formation being considered herein. Involved method for information quantity estimation is based on Shannon entropy formula. Information and entropy spectrum are decomposed and analysed for extraction of specific information and knowledge-that formation. The result of the entropy analysis point out the information needed to be acquired by the involved organisation, this being presented as a specific knowledge type.

  20. Semantic information extracting system for classification of radiological reports in radiology information system (RIS)

    Science.gov (United States)

    Shi, Liehang; Ling, Tonghui; Zhang, Jianguo

    2016-03-01

    Radiologists currently use a variety of terminologies and standards in most hospitals in China, and even there are multiple terminologies being used for different sections in one department. In this presentation, we introduce a medical semantic comprehension system (MedSCS) to extract semantic information about clinical findings and conclusion from free text radiology reports so that the reports can be classified correctly based on medical terms indexing standards such as Radlex or SONMED-CT. Our system (MedSCS) is based on both rule-based methods and statistics-based methods which improve the performance and the scalability of MedSCS. In order to evaluate the over all of the system and measure the accuracy of the outcomes, we developed computation methods to calculate the parameters of precision rate, recall rate, F-score and exact confidence interval.

  1. Multilingual biomedical dictionary.

    Science.gov (United States)

    Daumke, Philipp; Markó, Kornél; Poprat, Michael; Schulz, Stefan

    2005-01-01

    We present a unique technique to create a multilingual biomedical dictionary, based on a methodology called Morpho-Semantic indexing. Our approach closes a gap caused by the absence of free available multilingual medical dictionaries and the lack of accuracy of non-medical electronic translation tools. We first explain the underlying technology followed by a description of the dictionary interface, which makes use of a multilingual subword thesaurus and of statistical information from a domain-specific, multilingual corpus.

  2. Network fingerprint: a knowledge-based characterization of biomedical networks

    Science.gov (United States)

    Cui, Xiuliang; He, Haochen; He, Fuchu; Wang, Shengqi; Li, Fei; Bo, Xiaochen

    2015-01-01

    It can be difficult for biomedical researchers to understand complex molecular networks due to their unfamiliarity with the mathematical concepts employed. To represent molecular networks with clear meanings and familiar forms for biomedical researchers, we introduce a knowledge-based computational framework to decipher biomedical networks by making systematic comparisons to well-studied “basic networks”. A biomedical network is characterized as a spectrum-like vector called “network fingerprint”, which contains similarities to basic networks. This knowledge-based multidimensional characterization provides a more intuitive way to decipher molecular networks, especially for large-scale network comparisons and clustering analyses. As an example, we extracted network fingerprints of 44 disease networks in the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. The comparisons among the network fingerprints of disease networks revealed informative disease-disease and disease-signaling pathway associations, illustrating that the network fingerprinting framework will lead to new approaches for better understanding of biomedical networks. PMID:26307246

  3. Automated information extraction of key trial design elements from clinical trial publications.

    Science.gov (United States)

    de Bruijn, Berry; Carini, Simona; Kiritchenko, Svetlana; Martin, Joel; Sim, Ida

    2008-11-06

    Clinical trials are one of the most valuable sources of scientific evidence for improving the practice of medicine. The Trial Bank project aims to improve structured access to trial findings by including formalized trial information into a knowledge base. Manually extracting trial information from published articles is costly, but automated information extraction techniques can assist. The current study highlights a single architecture to extract a wide array of information elements from full-text publications of randomized clinical trials (RCTs). This architecture combines a text classifier with a weak regular expression matcher. We tested this two-stage architecture on 88 RCT reports from 5 leading medical journals, extracting 23 elements of key trial information such as eligibility rules, sample size, intervention, and outcome names. Results prove this to be a promising avenue to help critical appraisers, systematic reviewers, and curators quickly identify key information elements in published RCT articles.

  4. Extraction of spatio-temporal information of earthquake event based on semantic technology

    Science.gov (United States)

    Fan, Hong; Guo, Dan; Li, Huaiyuan

    2015-12-01

    In this paper a web information extraction method is presented which identifies a variety of thematic events utilizing the event knowledge framework derived from text training, and then further uses the syntactic analysis to extract the event key information. The method which combines the text semantic information and domain knowledge of the event makes the extraction of information people interested more accurate. In this paper, web based earthquake news extraction is taken as an example. The paper firstly briefs the overall approaches, and then details the key algorithm and experiments of seismic events extraction. Finally, this paper conducts accuracy analysis and evaluation experiments which demonstrate that the proposed method is a promising way of hot events mining.

  5. Analyzing rare diseases terms in biomedical terminologies

    Directory of Open Access Journals (Sweden)

    Erika Pasceri

    2012-03-01

    Full Text Available Rare disease patients too often face common problems, including the lack of access to correct diagnosis, lack of quality information on the disease, lack of scientific knowledge of the disease, inequities and difficulties in access to treatment and care. These things could be changed by implementing a comprehensive approach to rare diseases, increasing international cooperation in scientific research, by gaining and sharing scientific knowledge about and by developing tools for extracting and sharing knowledge. A significant aspect to analyze is the organization of knowledge in the biomedical field for the proper management and recovery of health information. For these purposes, the sources needed have been acquired from the Office of Rare Diseases Research, the National Organization of Rare Disorders and Orphanet, organizations that provide information to patients and physicians and facilitate the exchange of information among different actors involved in this field. The present paper shows the representation of rare diseases terms in biomedical terminologies such as MeSH, ICD-10, SNOMED CT and OMIM, leveraging the fact that these terminologies are integrated in the UMLS. At the first level, it was analyzed the overlap among sources and at a second level, the presence of rare diseases terms in target sources included in UMLS, working at the term and concept level. We found that MeSH has the best representation of rare diseases terms.

  6. Extracting Coherent Information from Noise Based Correlation Processing

    Science.gov (United States)

    2015-09-30

    LONG-TERM GOALS The goal of this research is to establish methodologies to utilize ambient noise in the ocean and to determine what scenarios...None PUBLICATIONS [1] “ Monitoring deep-ocean temperatures using acoustic ambinet noise,”K. W. Woolfe, S. Lani, K.G. Sabra, W. A. Kuperman...Geophys. Res. Lett., 42,2878–2884, doi:10.1002/2015GL063438 (2015). [2] “Optimized extraction of coherent arrivals from ambient noise correlations in

  7. Biomedical ontologies: a functional perspective.

    Science.gov (United States)

    Rubin, Daniel L; Shah, Nigam H; Noy, Natalya F

    2008-01-01

    The information explosion in biology makes it difficult for researchers to stay abreast of current biomedical knowledge and to make sense of the massive amounts of online information. Ontologies--specifications of the entities, their attributes and relationships among the entities in a domain of discourse--are increasingly enabling biomedical researchers to accomplish these tasks. In fact, bio-ontologies are beginning to proliferate in step with accruing biological data. The myriad of ontologies being created enables researchers not only to solve some of the problems in handling the data explosion but also introduces new challenges. One of the key difficulties in realizing the full potential of ontologies in biomedical research is the isolation of various communities involved: some workers spend their career developing ontologies and ontology-related tools, while few researchers (biologists and physicians) know how ontologies can accelerate their research. The objective of this review is to give an overview of biomedical ontology in practical terms by providing a functional perspective--describing how bio-ontologies can and are being used. As biomedical scientists begin to recognize the many different ways ontologies enable biomedical research, they will drive the emergence of new computer applications that will help them exploit the wealth of research data now at their fingertips.

  8. Advanced remote sensing terrestrial information extraction and applications

    CERN Document Server

    Liang, Shunlin; Wang, Jindi

    2012-01-01

    Advanced Remote Sensing is an application-based reference that provides a single source of mathematical concepts necessary for remote sensing data gathering and assimilation. It presents state-of-the-art techniques for estimating land surface variables from a variety of data types, including optical sensors such as RADAR and LIDAR. Scientists in a number of different fields including geography, geology, atmospheric science, environmental science, planetary science and ecology will have access to critically-important data extraction techniques and their virtually unlimited application

  9. Spoken Language Understanding Systems for Extracting Semantic Information from Speech

    CERN Document Server

    Tur, Gokhan

    2011-01-01

    Spoken language understanding (SLU) is an emerging field in between speech and language processing, investigating human/ machine and human/ human communication by leveraging technologies from signal processing, pattern recognition, machine learning and artificial intelligence. SLU systems are designed to extract the meaning from speech utterances and its applications are vast, from voice search in mobile devices to meeting summarization, attracting interest from both commercial and academic sectors. Both human/machine and human/human communications can benefit from the application of SLU, usin

  10. NEW METHOD OF EXTRACTING WEAK FAILURE INFORMATION IN GEARBOX BY COMPLEX WAVELET DENOISING

    Institute of Scientific and Technical Information of China (English)

    CHEN Zhixin; XU Jinwu; YANG Debin

    2008-01-01

    Because the extract of the weak failure information is always the difficulty and focus of fault detection. Aiming for specific statistical properties of complex wavelet coefficients of gearbox vibration signals, a new signal-denoising method which uses local adaptive algorithm based on dual-tree complex wavelet transform (DT-CWT) is introduced to extract weak failure information in gear, especially to extract impulse components. By taking into account the non-Gaussian probability distribution and the statistical dependencies among wavelet coefficients of some signals, and by taking the advantage of near shift-invariance of DT-CWT, the higher signal-to-noise ratio (SNR) than common wavelet denoising methods can be obtained. Experiments of extracting periodic impulses in gearbox vibration signals indicate that the method can extract incipient fault feature and hidden information from heavy noise, and it has an excellent effect on identifying weak feature signals in gearbox vibration signals.

  11. Extraction of information about periodic orbits from scattering functions

    CERN Document Server

    Bütikofer, T; Seligman, T H; Bütikofer, Thomas; Jung, Christof; Seligman, Thomas H.

    1999-01-01

    As a contribution to the inverse scattering problem for classical chaotic systems, we show that one can select sequences of intervals of continuity, each of which yields the information about period, eigenvalue and symmetry of one unstable periodic orbit.

  12. Biomedical applications of X-ray absorption and vibrational spectroscopic microscopies in obtaining structural information from complex systems

    Science.gov (United States)

    Aitken, Jade B.; Carter, Elizabeth A.; Eastgate, Harold; Hackett, Mark J.; Harris, Hugh H.; Levina, Aviva; Lee, Yao-Chang; Chen, Ching-Iue; Lai, Barry; Vogt, Stefan; Lay, Peter A.

    2010-02-01

    Protein crystallography and NMR spectroscopy took decades to emerge as routine techniques in structural biology. X-ray absorption spectroscopy now has reached a similar stage of maturity for obtaining complementary local structural information around metals in metalloproteins. However, the relatively recent emergence of X-ray and vibrational spectroscopic microprobes that build on these techniques has enabled the structural information obtained from the "mature" techniques on isolated biomolecules to be translated into in situ structural information from inhomogeneous complex systems, such as whole cells and tissues.

  13. Extraction of Information on the Technical Effect from a Patent Document

    Science.gov (United States)

    Sakai, Hiroyuki; Nonaka, Hirohumi; Masuyama, Shigeru

    We propose a method for extracting information on the technical effect from a patent document. The information on the technical effect extracted by our method is useful for generating patent maps (see e.g., Figure 1.) automatically or analyzing the technical trend from patent documents. Our method extracts expressions containing the information on the technical effect by using frequent expressions and clue expressions effective for extracting them. The frequent expressions and clue expressions are extracted by using statistical information and initial clue expressions automatically. Our method extracts expressions containing the information on the technical effect without predetermined patterns given by hand, and is expected to be applied to other tasks for acquiring expressions that have a particular meaning (e.g., information on the means for solving the problems) not limited to the information on the technical effect. Our method achieves not only high precision (78.0%) but also high recall (77.6%) by acquiring such clue expressions automatically from patent documents.

  14. Analysis of space-borne data for coastal zone information extraction of Goa Coast, India

    Digital Repository Service at National Institute of Oceanography (India)

    Kunte, P.D.; Wagle, B.G.

    Space-borne data covering the coastal zone of Goa State were processed using digital and visual image-processing techniques to extract information about the coastal zone. Digital image processing of thematic data included principal component...

  15. Information extraction from FN plots of tungsten microemitters

    Energy Technology Data Exchange (ETDEWEB)

    Mussa, Khalil O. [Department of Physics, Mu' tah University, Al-Karak (Jordan); Mousa, Marwan S., E-mail: mmousa@mutah.edu.jo [Department of Physics, Mu' tah University, Al-Karak (Jordan); Fischer, Andreas, E-mail: andreas.fischer@physik.tu-chemnitz.de [Institut für Physik, Technische Universität Chemnitz, Chemnitz (Germany)

    2013-09-15

    Tungsten based microemitter tips have been prepared both clean and coated with dielectric materials. For clean tungsten tips, apex radii have been varied ranging from 25 to 500 nm. These tips were manufactured by electrochemical etching a 0.1 mm diameter high purity (99.95%) tungsten wire at the meniscus of two molar NaOH solution. Composite micro-emitters considered here are consisting of a tungsten core coated with different dielectric materials—such as magnesium oxide (MgO), sodium hydroxide (NaOH), tetracyanoethylene (TCNE), and zinc oxide (ZnO). It is worthwhile noting here, that the rather unconventional NaOH coating has shown several interesting properties. Various properties of these emitters were measured including current–voltage (IV) characteristics and the physical shape of the tips. A conventional field emission microscope (FEM) with a tip (cathode)–screen (anode) separation standardized at 10 mm was used to electrically characterize the electron emitters. The system was evacuated down to a base pressure of ∼10{sup −8}mbar when baked at up to ∼180°C overnight. This allowed measurements of typical field electron emission (FE) characteristics, namely the IV characteristics and the emission images on a conductive phosphorus screen (the anode). Mechanical characterization has been performed through a FEI scanning electron microscope (SEM). Within this work, the mentioned experimental results are connected to the theory for analyzing Fowler–Nordheim (FN) plots. We compared and evaluated the data extracted from clean tungsten tips of different radii and determined deviations between the results of different extraction methods applied. In particular, we derived the apex radii of several clean and coated tungsten tips by both SEM imaging and analyzing FN plots. The aim of this analysis is to support the ongoing discussion on recently developed improvements of the theory for analyzing FN plots related to metal field electron emitters, which in

  16. Advanced Extraction of Spatial Information from High Resolution Satellite Data

    Science.gov (United States)

    Pour, T.; Burian, J.; Miřijovský, J.

    2016-06-01

    In this paper authors processed five satellite image of five different Middle-European cities taken by five different sensors. The aim of the paper was to find methods and approaches leading to evaluation and spatial data extraction from areas of interest. For this reason, data were firstly pre-processed using image fusion, mosaicking and segmentation processes. Results going into the next step were two polygon layers; first one representing single objects and the second one representing city blocks. In the second step, polygon layers were classified and exported into Esri shapefile format. Classification was partly hierarchical expert based and partly based on the tool SEaTH used for separability distinction and thresholding. Final results along with visual previews were attached to the original thesis. Results are evaluated visually and statistically in the last part of the paper. In the discussion author described difficulties of working with data of large size, taken by different sensors and different also thematically.

  17. Semantator: semantic annotator for converting biomedical text to linked data.

    Science.gov (United States)

    Tao, Cui; Song, Dezhao; Sharma, Deepak; Chute, Christopher G

    2013-10-01

    More than 80% of biomedical data is embedded in plain text. The unstructured nature of these text-based documents makes it challenging to easily browse and query the data of interest in them. One approach to facilitate browsing and querying biomedical text is to convert the plain text to a linked web of data, i.e., converting data originally in free text to structured formats with defined meta-level semantics. In this paper, we introduce Semantator (Semantic Annotator), a semantic-web-based environment for annotating data of interest in biomedical documents, browsing and querying the annotated data, and interactively refining annotation results if needed. Through Semantator, information of interest can be either annotated manually or semi-automatically using plug-in information extraction tools. The annotated results will be stored in RDF and can be queried using the SPARQL query language. In addition, semantic reasoners can be directly applied to the annotated data for consistency checking and knowledge inference. Semantator has been released online and was used by the biomedical ontology community who provided positive feedbacks. Our evaluation results indicated that (1) Semantator can perform the annotation functionalities as designed; (2) Semantator can be adopted in real applications in clinical and transactional research; and (3) the annotated results using Semantator can be easily used in Semantic-web-based reasoning tools for further inference.

  18. Financial Information Extraction Using Pre-defined and User-definable Templates in the LOLITA System

    OpenAIRE

    Costantino, Marco; Morgan, Richard G.; Collingham, Russell J.

    1996-01-01

    This paper addresses the issue of information extraction in the financial domain within the framework of a large Natural Language Processing system: LOLITA. The LOLITA system, Large-scale Object-based Linguistic Interactor Translator and Analyser, is a general purpose natural language processing system. Different kinds of applications have been built around the system's core. One of these is the financial information extraction application, which has been designed in close contact with expert...

  19. Extracting information masked by the chaotic signal of a time-delay system.

    Science.gov (United States)

    Ponomarenko, V I; Prokhorov, M D

    2002-08-01

    We further develop the method proposed by Bezruchko et al. [Phys. Rev. E 64, 056216 (2001)] for the estimation of the parameters of time-delay systems from time series. Using this method we demonstrate a possibility of message extraction for a communication system with nonlinear mixing of information signal and chaotic signal of the time-delay system. The message extraction procedure is illustrated using both numerical and experimental data and different kinds of information signals.

  20. Extracting Conflict-free Information from Multi-labeled Trees

    CERN Document Server

    Deepak, Akshay; McMahon, Michelle M

    2012-01-01

    A multi-labeled tree, or MUL-tree, is a phylogenetic tree where two or more leaves share a label, e.g., a species name. A MUL-tree can imply multiple conflicting phylogenetic relationships for the same set of taxa, but can also contain conflict-free information that is of interest and yet is not obvious. We define the information content of a MUL-tree T as the set of all conflict-free quartet topologies implied by T, and define the maximal reduced form of T as the smallest tree that can be obtained from T by pruning leaves and contracting edges while retaining the same information content. We show that any two MUL-trees with the same information content exhibit the same reduced form. This introduces an equivalence relation in MUL-trees with potential applications to comparing MUL-trees. We present an efficient algorithm to reduce a MUL-tree to its maximally reduced form and evaluate its performance on empirical datasets in terms of both quality of the reduced tree and the degree of data reduction achieved.

  1. On Depth Information Extraction from Metal Detector Signals

    NARCIS (Netherlands)

    Schoolderman, A.J.; Wolf, F.J. de; Merlat, L.

    2003-01-01

    Information on the depth of objects detected with the help of a metal detector is useful for safe excavation of these objects in demining operations. Apart from that, depth informatíon may be used in advanced sensor fusion algorithms for a detection system where a metal detector is combíned with eg.

  2. CTSS: A Tool for Efficient Information Extraction with Soft Matching Rules for Text Mining

    Directory of Open Access Journals (Sweden)

    A. Christy

    2008-01-01

    Full Text Available The abundance of information available digitally in modern world had made a demand for structured information. The problem of text mining which dealt with discovering useful information from unstructured text had attracted the attention of researchers. The role of Information Extraction (IE software was to identify relevant information from texts, extracting information from a variety of sources and aggregating it to create a single view. Information extraction systems depended on particular corpora and were poor in recall values. Therefore, developing the system as domain-independent as well as improving the recall was an important challenge for IE. In this research, the authors proposed a domain-independent algorithm for information extraction, called SOFTRULEMINING for extracting the aim, methodology and conclusion from technical abstracts. The algorithm was implemented by combining trigram model with softmatching rules. A tool CTSS was constructed using SOFTRULEMINING and was tested with technical abstracts of www.computer.org and www.ansinet.org and found that the tool had improved its recall value and therefore the precision value in comparison with other search engines.

  3. Information Extraction of High Resolution Remote Sensing Images Based on the Calculation of Optimal Segmentation Parameters.

    Science.gov (United States)

    Zhu, Hongchun; Cai, Lijie; Liu, Haiying; Huang, Wei

    2016-01-01

    Multi-scale image segmentation and the selection of optimal segmentation parameters are the key processes in the object-oriented information extraction of high-resolution remote sensing images. The accuracy of remote sensing special subject information depends on this extraction. On the basis of WorldView-2 high-resolution data, the optimal segmentation parameters methodof object-oriented image segmentation and high-resolution image information extraction, the following processes were conducted in this study. Firstly, the best combination of the bands and weights was determined for the information extraction of high-resolution remote sensing image. An improved weighted mean-variance method was proposed andused to calculatethe optimal segmentation scale. Thereafter, the best shape factor parameter and compact factor parameters were computed with the use of the control variables and the combination of the heterogeneity and homogeneity indexes. Different types of image segmentation parameters were obtained according to the surface features. The high-resolution remote sensing images were multi-scale segmented with the optimal segmentation parameters. Ahierarchical network structure was established by setting the information extraction rules to achieve object-oriented information extraction. This study presents an effective and practical method that can explain expert input judgment by reproducible quantitative measurements. Furthermore the results of this procedure may be incorporated into a classification scheme.

  4. Information Extraction of High Resolution Remote Sensing Images Based on the Calculation of Optimal Segmentation Parameters.

    Directory of Open Access Journals (Sweden)

    Hongchun Zhu

    Full Text Available Multi-scale image segmentation and the selection of optimal segmentation parameters are the key processes in the object-oriented information extraction of high-resolution remote sensing images. The accuracy of remote sensing special subject information depends on this extraction. On the basis of WorldView-2 high-resolution data, the optimal segmentation parameters methodof object-oriented image segmentation and high-resolution image information extraction, the following processes were conducted in this study. Firstly, the best combination of the bands and weights was determined for the information extraction of high-resolution remote sensing image. An improved weighted mean-variance method was proposed andused to calculatethe optimal segmentation scale. Thereafter, the best shape factor parameter and compact factor parameters were computed with the use of the control variables and the combination of the heterogeneity and homogeneity indexes. Different types of image segmentation parameters were obtained according to the surface features. The high-resolution remote sensing images were multi-scale segmented with the optimal segmentation parameters. Ahierarchical network structure was established by setting the information extraction rules to achieve object-oriented information extraction. This study presents an effective and practical method that can explain expert input judgment by reproducible quantitative measurements. Furthermore the results of this procedure may be incorporated into a classification scheme.

  5. Biomedical Literature Exploration through Latent Semantics

    Directory of Open Access Journals (Sweden)

    Hugo ARAÚJO

    2013-08-01

    Full Text Available The fast increasing amount of articles published in the biomedical field is creating difficulties in the way this wealth of information can be efficiently exploited by researchers. As a way of overcoming these limitations and potentiating a more efficient use of the literature, we propose an approach for structuring the results of a literature search based on the latent semantic information extracted from a corpus. Moreover, we show how the results of the Latent Semantic Analysis method can be adapted so as to evidence differences between results of different searches. We also propose different visualization techniques that can be applied to explore these results. Used in combination, these techniques could empower users with tools for literature guided knowledge exploration and discovery.

  6. Converging micro-nano-bio technologies towards integrated biomedical systems: state of the art and future perspectives under the EU-information & communication technologies program.

    Science.gov (United States)

    Lymberis, A

    2008-01-01

    Research and development at the convergence of microelectronics, nano-materials, biochemistry, measurement technology and information technology is leading to a new class of biomedical systems and applications e.g. molecular imaging, point of care testing, gene therapy and bionics (including on and inside the body sensors and other miniaturised smart systems) which are expected to revolutionise the healthcare provision and quality of life. In particular they are expected to identify diseases at the earliest possible stage, intervene before symptomatic disease becomes apparent and monitor both the progress of the diseases and the effect of intervention and therapeutic procedures. The group of EC-funded projects on Micro-Nano-Bio Convergence Systems, "so-called" MNBS, is made by projects developing systems that use a vast array of technologies to integrate across traditional boundaries between the micro-nano-bio, and info worlds, enabling a wide range of applications from health care to food quality monitoring. It includes mainly two sub-groups, one dealing with systems for in vitro molecular diagnosis and biological/biochemical analysis and the other is dealing with systems for in vivo interaction with the human body. Current status of development and future challenges, technological and socioeconomic, are briefly presented in this paper as background introductory information to the mini-symposium on MNBS. Relevant examples of R&D within the group will be presented in the mini-symposium.

  7. In-line phase contrast micro-CT reconstruction for biomedical specimens.

    Science.gov (United States)

    Fu, Jian; Tan, Renbo

    2014-01-01

    X-ray phase contrast micro computed tomography (micro-CT) can non-destructively provide the internal structure information of soft tissues and low atomic number materials. It has become an invaluable analysis tool for biomedical specimens. Here an in-line phase contrast micro-CT reconstruction technique is reported, which consists of a projection extraction method and the conventional filter back-projection (FBP) reconstruction algorithm. The projection extraction is implemented by applying the Fourier transform to the forward projections of in-line phase contrast micro-CT. This work comprises a numerical study of the method and its experimental verification using a biomedical specimen dataset measured at an X-ray tube source micro-CT setup. The numerical and experimental results demonstrate that the presented technique can improve the imaging contrast of biomedical specimens. It will be of interest for a wide range of in-line phase contrast micro-CT applications in medicine and biology.

  8. Imaged document information location and extraction using an optical correlator

    Science.gov (United States)

    Stalcup, Bruce W.; Dennis, Phillip W.; Dydyk, Robert B.

    1999-12-01

    Today, the paper document is fast becoming a thing of the past. With the rapid development of fast, inexpensive computing and storage devices, many government and private organizations are archiving their documents in electronic form (e.g., personnel records, medical records, patents, etc.). Many of these organizations are converting their paper archives to electronic images, which are then stored in a computer database. Because of this, there is a need to efficiently organize this data into comprehensive and accessible information resources and provide for rapid access to the information contained within these imaged documents. To meet this need, Litton PRC and Litton Data Systems Division are developing a system, the Imaged Document Optical Correlation and Conversion System (IDOCCS), to provide a total solution to the problem of managing and retrieving textual and graphic information from imaged document archives. At the heart of IDOCCS, optical correlation technology provide a means for the search and retrieval of information from imaged documents. IDOCCS can be used to rapidly search for key words or phrases within the imaged document archives and has the potential to determine the types of languages contained within a document. In addition, IDOCCS can automatically compare an input document with the archived database to determine if it is a duplicate, thereby reducing the overall resources required to maintain and access the document database. Embedded graphics on imaged pages can also be exploited, e.g., imaged documents containing an agency's seal or logo can be singled out. In this paper, we present a description of IDOCCS as well as preliminary performance results and theoretical projections.

  9. ADVANCED EXTRACTION OF SPATIAL INFORMATION FROM HIGH RESOLUTION SATELLITE DATA

    Directory of Open Access Journals (Sweden)

    T. Pour

    2016-06-01

    Full Text Available In this paper authors processed five satellite image of five different Middle-European cities taken by five different sensors. The aim of the paper was to find methods and approaches leading to evaluation and spatial data extraction from areas of interest. For this reason, data were firstly pre-processed using image fusion, mosaicking and segmentation processes. Results going into the next step were two polygon layers; first one representing single objects and the second one representing city blocks. In the second step, polygon layers were classified and exported into Esri shapefile format. Classification was partly hierarchical expert based and partly based on the tool SEaTH used for separability distinction and thresholding. Final results along with visual previews were attached to the original thesis. Results are evaluated visually and statistically in the last part of the paper. In the discussion author described difficulties of working with data of large size, taken by different sensors and different also thematically.

  10. Omnidirectional vision systems calibration, feature extraction and 3D information

    CERN Document Server

    Puig, Luis

    2013-01-01

    This work focuses on central catadioptric systems, from the early step of calibration to high-level tasks such as 3D information retrieval. The book opens with a thorough introduction to the sphere camera model, along with an analysis of the relation between this model and actual central catadioptric systems. Then, a new approach to calibrate any single-viewpoint catadioptric camera is described.  This is followed by an analysis of existing methods for calibrating central omnivision systems, and a detailed examination of hybrid two-view relations that combine images acquired with uncalibrated

  11. Extraction of Left Ventricular Ejection Fraction Information from Various Types of Clinical Reports.

    Science.gov (United States)

    Kim, Youngjun; Garvin, Jennifer H; Goldstein, Mary K; Hwang, Tammy S; Redd, Andrew; Bolton, Dan; Heidenreich, Paul A; Meystre, Stéphane M

    2017-02-02

    Efforts to improve the treatment of congestive heart failure, a common and serious medical condition, include the use of quality measures to assess guideline-concordant care. The goal of this study is to identify left ventricular ejection fraction (LVEF) information from various types of clinical notes, and to then use this information for heart failure quality measurement. We analyzed the annotation differences between a new corpus of clinical notes from the Echocardiography, Radiology, and Text Integrated Utility package and other corpora annotated for natural language processing (NLP) research in the Department of Veterans Affairs. These reports contain varying degrees of structure. To examine whether existing LVEF extraction modules we developed in prior research improve the accuracy of LVEF information extraction from the new corpus, we created two sequence-tagging NLP modules trained with a new data set, with or without predictions from the existing LVEF extraction modules. We also conducted a set of experiments to examine the impact of training data size on information extraction accuracy. We found that less training data is needed when reports are highly structured, and that combining predictions from existing LVEF extraction modules improves information extraction when reports have less structured formats and a rich set of vocabulary.

  12. Data-Driven Information Extraction from Chinese Electronic Medical Records.

    Directory of Open Access Journals (Sweden)

    Dong Xu

    Full Text Available This study aims to propose a data-driven framework that takes unstructured free text narratives in Chinese Electronic Medical Records (EMRs as input and converts them into structured time-event-description triples, where the description is either an elaboration or an outcome of the medical event.Our framework uses a hybrid approach. It consists of constructing cross-domain core medical lexica, an unsupervised, iterative algorithm to accrue more accurate terms into the lexica, rules to address Chinese writing conventions and temporal descriptors, and a Support Vector Machine (SVM algorithm that innovatively utilizes Normalized Google Distance (NGD to estimate the correlation between medical events and their descriptions.The effectiveness of the framework was demonstrated with a dataset of 24,817 de-identified Chinese EMRs. The cross-domain medical lexica were capable of recognizing terms with an F1-score of 0.896. 98.5% of recorded medical events were linked to temporal descriptors. The NGD SVM description-event matching achieved an F1-score of 0.874. The end-to-end time-event-description extraction of our framework achieved an F1-score of 0.846.In terms of named entity recognition, the proposed framework outperforms state-of-the-art supervised learning algorithms (F1-score: 0.896 vs. 0.886. In event-description association, the NGD SVM is superior to SVM using only local context and semantic features (F1-score: 0.874 vs. 0.838.The framework is data-driven, weakly supervised, and robust against the variations and noises that tend to occur in a large corpus. It addresses Chinese medical writing conventions and variations in writing styles through patterns used for discovering new terms and rules for updating the lexica.

  13. Telemedicine optoelectronic biomedical data processing system

    Science.gov (United States)

    Prosolovska, Vita V.

    2010-08-01

    The telemedicine optoelectronic biomedical data processing system is created to share medical information for the control of health rights and timely and rapid response to crisis. The system includes the main blocks: bioprocessor, analog-digital converter biomedical images, optoelectronic module for image processing, optoelectronic module for parallel recording and storage of biomedical imaging and matrix screen display of biomedical images. Rated temporal characteristics of the blocks defined by a particular triggering optoelectronic couple in analog-digital converters and time imaging for matrix screen. The element base for hardware implementation of the developed matrix screen is integrated optoelectronic couples produced by selective epitaxy.

  14. Frontiers in biomedical engineering and biotechnology.

    Science.gov (United States)

    Liu, Feng; Goodarzi, Ali; Wang, Haifeng; Stasiak, Joanna; Sun, Jianbo; Zhou, Yu

    2014-01-01

    The 2nd International Conference on Biomedical Engineering and Biotechnology (iCBEB 2013), held in Wuhan on 11–13 October 2013, is an annual conference that aims at providing an opportunity for international and national researchers and practitioners to present the most recent advances and future challenges in the fields of Biomedical Information, Biomedical Engineering and Biotechnology. The papers published by this issue are selected from this conference, which witnesses the frontier in the field of Biomedical Engineering and Biotechnology, which particularly has helped improving the level of clinical diagnosis in medical work.

  15. STUDY ON EXTRACTING METHODS OF BURIED GEOLOGICAL INFORMATION IN HUAIBEI COAL FIELD

    Institute of Scientific and Technical Information of China (English)

    王四龙; 赵学军; 凌贻棕; 刘玉荣; 宁书年; 侯德文

    1999-01-01

    It is discussed features and the producing mechanism of buried geological information in geological, geophysical and remote sensing data in Huaibei coal field, and studied the methods extracting buried tectonic and igneous rock information from various geological data using digital image processing techniques.

  16. Post-processing of Deep Web Information Extraction Based on Domain Ontology

    Directory of Open Access Journals (Sweden)

    PENG, T.

    2013-11-01

    Full Text Available Many methods are utilized to extract and process query results in deep Web, which rely on the different structures of Web pages and various designing modes of databases. However, some semantic meanings and relations are ignored. So, in this paper, we present an approach for post-processing deep Web query results based on domain ontology which can utilize the semantic meanings and relations. A block identification model (BIM based on node similarity is defined to extract data blocks that are relevant to specific domain after reducing noisy nodes. Feature vector of domain books is obtained by result set extraction model (RSEM based on vector space model (VSM. RSEM, in combination with BIM, builds the domain ontology on books which can not only remove the limit of Web page structures when extracting data information, but also make use of semantic meanings of domain ontology. After extracting basic information of Web pages, a ranking algorithm is adopted to offer an ordered list of data records to users. Experimental results show that BIM and RSEM extract data blocks and build domain ontology accurately. In addition, relevant data records and basic information are extracted and ranked. The performances precision and recall show that our proposed method is feasible and efficient.

  17. Analysis of Automated Modern Web Crawling and Testing Tools and Their Possible Employment for Information Extraction

    Directory of Open Access Journals (Sweden)

    Tomas Grigalis

    2012-04-01

    Full Text Available World Wide Web has become an enormously big repository of data. Extracting, integrating and reusing this kind of data has a wide range of applications, including meta-searching, comparison shopping, business intelligence tools and security analysis of information in websites. However, reaching information in modern WEB 2.0 web pages, where HTML tree is often dynamically modified by various JavaScript codes, new data are added by asynchronous requests to the web server and elements are positioned with the help of cascading style sheets, is a difficult task. The article reviews automated web testing tools for information extraction tasks.Article in Lithuanian

  18. The research of road and vehicle information extraction algorithm based on high resolution remote sensing image

    Science.gov (United States)

    Zhou, Tingting; Gu, Lingjia; Ren, Ruizhi; Cao, Qiong

    2016-09-01

    With the rapid development of remote sensing technology, the spatial resolution and temporal resolution of satellite imagery also have a huge increase. Meanwhile, High-spatial-resolution images are becoming increasingly popular for commercial applications. The remote sensing image technology has broad application prospects in intelligent traffic. Compared with traditional traffic information collection methods, vehicle information extraction using high-resolution remote sensing image has the advantages of high resolution and wide coverage. This has great guiding significance to urban planning, transportation management, travel route choice and so on. Firstly, this paper preprocessed the acquired high-resolution multi-spectral and panchromatic remote sensing images. After that, on the one hand, in order to get the optimal thresholding for image segmentation, histogram equalization and linear enhancement technologies were applied into the preprocessing results. On the other hand, considering distribution characteristics of road, the normalized difference vegetation index (NDVI) and normalized difference water index (NDWI) were used to suppress water and vegetation information of preprocessing results. Then, the above two processing result were combined. Finally, the geometric characteristics were used to completed road information extraction. The road vector extracted was used to limit the target vehicle area. Target vehicle extraction was divided into bright vehicles extraction and dark vehicles extraction. Eventually, the extraction results of the two kinds of vehicles were combined to get the final results. The experiment results demonstrated that the proposed algorithm has a high precision for the vehicle information extraction for different high resolution remote sensing images. Among these results, the average fault detection rate was about 5.36%, the average residual rate was about 13.60% and the average accuracy was approximately 91.26%.

  19. Design and analysis of biomedical studies

    DEFF Research Database (Denmark)

    Hansen, Merete Kjær

    Biomedicine is a field that has great influence on the majority of mankind. The constant development has considerably changed our way of life during the last centuries. This has been achieved through the dedication of biomedical researchers along with the tremendous ressources that over time have...... been allocated this field. It is utterly important to utilize these ressources responsibly and efficiently by constantly striving to ensure high-quality biomedical studies. This involves the use of a sound statistical methodology regarding both the design and analysis of biomedical studies. The focus...... for biomedical studies are a recurring theme in this thesis. Data collected in some biomedical studies are positively skewed; hence methods relying on the normal distribution are not directly applicable. We investigated how data from one of these studies are suitably analyzed. We extracted 23 different summary...

  20. The Technology of Extracting Content Information from Web Page Based on DOM Tree

    Science.gov (United States)

    Yuan, Dingrong; Mo, Zhuoying; Xie, Bing; Xie, Yangcai

    There are huge amounts of information on Web pages, which includes content information and other useless information, such as navigation, advertisement and flash of animation etc. Reducing the toils of Web users, we estabished a thechnique to extract the content information from web page. Fristly, we analyzed the semantic of web documents by V8 engine of Google and parsed the web document into DOM tree. And then, traversed the DOM tree, pruned the DOM tree in the light of the characteristic of Web page's edit language. Finally, we extracted the content information from Web page. Theoretics and experiments showed that the technique could simplify the web page, present the content information to web users and supply clean data for applicable area, such as retrieval, KDD and DM from web.

  1. Biomedical applications of collagens.

    Science.gov (United States)

    Ramshaw, John A M

    2016-05-01

    Collagen-based biomedical materials have developed into important, clinically effective materials used in a range of devices that have gained wide acceptance. These devices come with collagen in various formats, including those based on stabilized natural tissues, those that are based on extracted and purified collagens, and designed composite, biosynthetic materials. Further knowledge on the structure and function of collagens has led to on-going developments and improvements. Among these developments has been the production of recombinant collagen materials that are well defined and are disease free. Most recently, a group of bacterial, non-animal collagens has emerged that may provide an excellent, novel source of collagen for use in biomaterials and other applications. These newer collagens are discussed in detail. They can be modified to direct their function, and they can be fabricated into various formats, including films and sponges, while solutions can also be adapted for use in surface coating technologies.

  2. What do professional forecasters' stock market expectations tell us about herding, information extraction and beauty contests?

    DEFF Research Database (Denmark)

    Rangvid, Jesper; Schmeling, M.; Schrimpf, A.

    2013-01-01

    We study how professional forecasters form equity market expectations based on a new micro-level dataset which includes rich cross-sectional information about individual characteristics. We focus on testing whether agents rely on the beliefs of others, i.e., consensus expectations, when forming t...... that neither information extraction to incorporate dispersed private information, nor herding for reputational reasons can fully explain these results, leaving Keynes' beauty contest argument as a potential candidate for explaining forecaster behavior....

  3. Extraction of Hidden Social Networks from Wiki-Environment Involved in Information Conflict

    OpenAIRE

    Alguliyev, Rasim M.; Ramiz M. Aliguliyev; Irada Y. Alakbarova

    2016-01-01

    Social network analysis is a widely used technique to analyze relationships among wiki-users in Wikipedia. In this paper the method to identify hidden social networks participating in information conflicts in wiki-environment is proposed. In particular, we describe how text clustering techniques can be used for extraction of hidden social networks of wiki-users caused information conflict. By clustering unstructured text articles caused information conflict we ...

  4. BIG: a Grid Portal for Biomedical Data and Images

    Directory of Open Access Journals (Sweden)

    Giovanni Aloisio

    2004-06-01

    Full Text Available Modern management of biomedical systems involves the use of many distributed resources, such as high performance computational resources to analyze biomedical data, mass storage systems to store them, medical instruments (microscopes, tomographs, etc., advanced visualization and rendering tools. Grids offer the computational power, security and availability needed by such novel applications. This paper presents BIG (Biomedical Imaging Grid, a Web-based Grid portal for management of biomedical information (data and images in a distributed environment. BIG is an interactive environment that deals with complex user's requests, regarding the acquisition of biomedical data, the "processing" and "delivering" of biomedical images, using the power and security of Computational Grids.

  5. Extracting information from the data flood of new solar telescopes. Brainstorming

    CERN Document Server

    Ramos, A Asensio

    2012-01-01

    Extracting magnetic and thermodynamic information from spectropolarimetric observations is a difficult and time consuming task. The amount of science-ready data that will be generated by the new family of large solar telescopes is so large that we will be forced to modify the present approach to inference. In this contribution, I propose several possible ways that might be useful for extracting the thermodynamic and magnetic properties of solar plasmas from such observations quickly.

  6. Extracting Information from the Data Flood of New Solar Telescopes: Brainstorming

    Science.gov (United States)

    Asensio Ramos, A.

    2012-12-01

    Extracting magnetic and thermodynamic information from spectropolarimetric observations is a difficult and time consuming task. The amount of science-ready data that will be generated by the new family of large solar telescopes is so large that we will be forced to modify the present approach to inference. In this contribution, I propose several possible ways that might be useful for extracting the thermodynamic and magnetic properties of solar plasmas from such observations quickly.

  7. Environmental/Biomedical Terminology Index

    Energy Technology Data Exchange (ETDEWEB)

    Huffstetler, J.K.; Dailey, N.S.; Rickert, L.W.; Chilton, B.D.

    1976-12-01

    The Information Center Complex (ICC), a centrally administered group of information centers, provides information support to environmental and biomedical research groups and others within and outside Oak Ridge National Laboratory. In-house data base building and development of specialized document collections are important elements of the ongoing activities of these centers. ICC groups must be concerned with language which will adequately classify and insure retrievability of document records. Language control problems are compounded when the complexity of modern scientific problem solving demands an interdisciplinary approach. Although there are several word lists, indexes, and thesauri specific to various scientific disciplines usually grouped as Environmental Sciences, no single generally recognized authority can be used as a guide to the terminology of all environmental science. If biomedical terminology for the description of research on environmental effects is also needed, the problem becomes even more complex. The building of a word list which can be used as a general guide to the environmental/biomedical sciences has been a continuing activity of the Information Center Complex. This activity resulted in the publication of the Environmental Biomedical Terminology Index (EBTI).

  8. Biomedical Imaging Principles and Applications

    CERN Document Server

    Salzer, Reiner

    2012-01-01

    This book presents and describes imaging technologies that can be used to study chemical processes and structural interactions in dynamic systems, principally in biomedical systems. The imaging technologies, largely biomedical imaging technologies such as MRT, Fluorescence mapping, raman mapping, nanoESCA, and CARS microscopy, have been selected according to their application range and to the chemical information content of their data. These technologies allow for the analysis and evaluation of delicate biological samples, which must not be disturbed during the profess. Ultimately, this may me

  9. Research of building information extraction and evaluation based on high-resolution remote-sensing imagery

    Science.gov (United States)

    Cao, Qiong; Gu, Lingjia; Ren, Ruizhi; Wang, Lang

    2016-09-01

    Building extraction currently is important in the application of high-resolution remote sensing imagery. At present, quite a few algorithms are available for detecting building information, however, most of them still have some obvious disadvantages, such as the ignorance of spectral information, the contradiction between extraction rate and extraction accuracy. The purpose of this research is to develop an effective method to detect building information for Chinese GF-1 data. Firstly, the image preprocessing technique is used to normalize the image and image enhancement is used to highlight the useful information in the image. Secondly, multi-spectral information is analyzed. Subsequently, an improved morphological building index (IMBI) based on remote sensing imagery is proposed to get the candidate building objects. Furthermore, in order to refine building objects and further remove false objects, the post-processing (e.g., the shape features, the vegetation index and the water index) is employed. To validate the effectiveness of the proposed algorithm, the omission errors (OE), commission errors (CE), the overall accuracy (OA) and Kappa are used at final. The proposed method can not only effectively use spectral information and other basic features, but also avoid extracting excessive interference details from high-resolution remote sensing images. Compared to the original MBI algorithm, the proposed method reduces the OE by 33.14% .At the same time, the Kappa increase by 16.09%. In experiments, IMBI achieved satisfactory results and outperformed other algorithms in terms of both accuracies and visual inspection

  10. Real-time traffic information extraction based on compressed video with interframe motion vector

    Institute of Scientific and Technical Information of China (English)

    黄庆明; 王聪

    2003-01-01

    Extraction of traffic information from image or video sequence is a hot research topic in intelligenttransportation system and computer vision. A real-time traffic information extraction method based on com-pressed video with interframe motion vectors for speed, density and flow detection, has been proposed for ex-traction of traffic information under fixed camera setting and well-defined environment. The motion vectors arefirst separated from the compressed video streams, and then filtered to eliminate incorrect and noisy vectors u-sing the well-defined environmental knowledge. By applying the projective transform and using the filtered mo-tion vectors, speed can be calculated from motion vector statistics, density can be estimated using the motionvector occupancy, and flow can be detected using the combination of speed and density. The embodiment of aprototype system for sky camera traffic monitoring using the MPEG video has been implemented, and experi-mental results proved the effectiveness of the method proposed.

  11. Biomedical image understanding methods and applications

    CERN Document Server

    Lim, Joo-Hwee; Xiong, Wei

    2015-01-01

    A comprehensive guide to understanding and interpreting digital images in medical and functional applications Biomedical Image Understanding focuses on image understanding and semantic interpretation, with clear introductions to related concepts, in-depth theoretical analysis, and detailed descriptions of important biomedical applications. It covers image processing, image filtering, enhancement, de-noising, restoration, and reconstruction; image segmentation and feature extraction; registration; clustering, pattern classification, and data fusion. With contributions from ex

  12. Photo-mediated green synthesis of silver and zinc oxide nanoparticles using aqueous extracts of two mangrove plant species, Heritiera fomes and Sonneratia apetala and investigation of their biomedical applications.

    Science.gov (United States)

    Thatoi, Priyabrata; Kerry, Rout George; Gouda, Sushanto; Das, Gitishree; Pramanik, Krishna; Thatoi, Hrudayanath; Patra, Jayanta Kumar

    2016-10-01

    Green synthesis by using biological agents has been a simple and effective approach for the synthesis of various forms of nanoparticles. The present investigation was intended to synthesis Ag-NPs and ZnO-NPs under photo-condition using the aqueous extracts of two mangrove plants namely Heritiera fomes and Sonneratia apetala and evaluate their potential biomedical applications. The formation of nanoparticles in aqueous solution of H. fomes and S. apetala under exposure to sun light was validated by change in color and formation of monodispersed NPs with a narrow particle size distribution. Fourier transform infrared spectroscopy (FT-IR) reveals the presence of Oxime and other heterocyclic compounds to be the most probable compounds responsible for the reduction and stability of nanoparticles in the solutions. The synthesized NPs displayed moderate free radical scavenging properties. The anti-inflammatory potential of ZnO-NPs was recorded to be comparatively higher than that of Ag-NP with 79% and 69.1% respectively. The Ag-NPs with unique properties of inhibiting α-amylase (91.14% and 89.16%) were found to be significantly high indicating its antidiabetic property. The synthesized NPs showed varied zone of inhibition (9-16mm) against the tested microbial pathogens. The synthesized nanoparticles possess strong biological activities in terms of antioxidant, anti-inflammatory, antidiabetic and antibacterial, potentials which could be utilized in various biological applications by the cosmetic, food and biomedical industries.

  13. Pathophysiologic mechanisms of biomedical nanomaterials.

    Science.gov (United States)

    Wang, Liming; Chen, Chunying

    2016-05-15

    Nanomaterials (NMs) have been widespread used in biomedical fields, daily consuming, and even food industry. It is crucial to understand the safety and biomedical efficacy of NMs. In this review, we summarized the recent progress about the physiological and pathological effects of NMs from several levels: protein-nano interface, NM-subcellular structures, and cell-cell interaction. We focused on the detailed information of nano-bio interaction, especially about protein adsorption, intracellular trafficking, biological barriers, and signaling pathways as well as the associated mechanism mediated by nanomaterials. We also introduced related analytical methods that are meaningful and helpful for biomedical effect studies in the future. We believe that knowledge about pathophysiologic effects of NMs is not only significant for rational design of medical NMs but also helps predict their safety and further improve their applications in the future.

  14. Biomedical engineering fundamentals

    CERN Document Server

    Bronzino, Joseph D

    2014-01-01

    Known as the bible of biomedical engineering, The Biomedical Engineering Handbook, Fourth Edition, sets the standard against which all other references of this nature are measured. As such, it has served as a major resource for both skilled professionals and novices to biomedical engineering.Biomedical Engineering Fundamentals, the first volume of the handbook, presents material from respected scientists with diverse backgrounds in physiological systems, biomechanics, biomaterials, bioelectric phenomena, and neuroengineering. More than three dozen specific topics are examined, including cardia

  15. Information Extraction of High-Resolution Remotely Sensed Image Based on Multiresolution Segmentation

    Directory of Open Access Journals (Sweden)

    Peng Shao

    2014-08-01

    Full Text Available The principle of multiresolution segmentation was represented in detail in this study, and the canny algorithm was applied for edge-detection of a remotely sensed image based on this principle. The target image was divided into regions based on object-oriented multiresolution segmentation and edge-detection. Furthermore, object hierarchy was created, and a series of features (water bodies, vegetation, roads, residential areas, bare land and other information were extracted by the spectral and geometrical features. The results indicate that the edge-detection has a positive effect on multiresolution segmentation, and overall accuracy of information extraction reaches to 94.6% by the confusion matrix.

  16. Extracting information from two-dimensional electrophoresis gels by partial least squares regression

    DEFF Research Database (Denmark)

    Jessen, Flemming; Lametsch, R.; Bendixen, E.;

    2002-01-01

    of all proteins/spots in the gels. In the present study it is demonstrated how information can be extracted by multivariate data analysis. The strategy is based on partial least squares regression followed by variable selection to find proteins that individually or in combination with other proteins vary......Two-dimensional gel electrophoresis (2-DE) produces large amounts of data and extraction of relevant information from these data demands a cautious and time consuming process of spot pattern matching between gels. The classical approach of data analysis is to detect protein markers that appear...

  17. Ultrasonic Signal Processing Algorithm for Crack Information Extraction on the Keyway of Turbine Rotor Disk

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Hong Kyu; Seo, Won Chan; Park, Chan [Pukyong National University, Busan (Korea, Republic of); Lee, Jong O; Son, Young Ho [KIMM, Daejeon (Korea, Republic of)

    2009-10-15

    An ultrasonic signal processing algorithm was developed for extracting the information of cracks generated around the keyway of a turbine rotor disk. B-scan images were obtained by using keyway specimens and an ultrasonic scan system with x-y position controller. The B-scan images were used as input images for 2-Dimensional signal processing, and the algorithm was constructed with four processing stages of pre-processing, crack candidate region detection, crack region classification and crack information extraction. It is confirmed by experiments that the developed algorithm is effective for the quantitative evaluation of cracks generated around the keyway of turbine rotor disk

  18. Information extraction for legal knowledge representation – a review of approaches and trends

    Directory of Open Access Journals (Sweden)

    Denis Andrei de Araujo

    2014-11-01

    Full Text Available This work presents an introduction to Information Extraction systems and a survey of the known approaches of Information Extraction in the legal area. This work analyzes with particular attention the techniques that rely on the representation of legal knowledge as a means to achieve better performance, with emphasis on those techniques including ontologies and linguistic support. Some details of the systems implementations are presented, followed by an analysis of the positive and negative points of each approach, aiming to bring the reader a critical position regarding the solutions studied.

  19. Extraction of Informative Blocks from Deep Web Page Using Similar Layout Feature

    OpenAIRE

    Zeng,Jun; Flanagan, Brendan; Hirokawa, Sachio

    2013-01-01

    Due to the explosive growth and popularity of the deep web, information extraction from deep web page has gained more and more attention. However, the HTML structure of web page has become more complicated, making it difficult to recognize target content by only analyzing the HTML source code. In this paper, we propose a method to extract the informative blocks from a deep web using the layout feature. We consider the visual rectangular region of an HTML element as a visual block in web page....

  20. Biomedical nanosensors

    CERN Document Server

    Irudayaraj, Joseph M

    2012-01-01

    This book draws together recent data on both cytoplasmic and flagellar dyneins and the proteins they interact with, to give the reader a clear picture of what is currently known about the structure and mechanics of these remarkable macro-molecular machines. Each chapter is written by active researchers, with a focus on currently used biophysical, biochemical, and cell biological methods. In addition to comprehensive coverage of structural information gained by electron microscopy, electron cryo-tomography, X-ray crystallography, and nuclear magnetic resonance, this book provides detailed descr

  1. Constructing a semantic predication gold standard from the biomedical literature

    Directory of Open Access Journals (Sweden)

    Kilicoglu Halil

    2011-12-01

    Full Text Available Abstract Background Semantic relations increasingly underpin biomedical text mining and knowledge discovery applications. The success of such practical applications crucially depends on the quality of extracted relations, which can be assessed against a gold standard reference. Most such references in biomedical text mining focus on narrow subdomains and adopt different semantic representations, rendering them difficult to use for benchmarking independently developed relation extraction systems. In this article, we present a multi-phase gold standard annotation study, in which we annotated 500 sentences randomly selected from MEDLINE abstracts on a wide range of biomedical topics with 1371 semantic predications. The UMLS Metathesaurus served as the main source for conceptual information and the UMLS Semantic Network for relational information. We measured interannotator agreement and analyzed the annotations closely to identify some of the challenges in annotating biomedical text with relations based on an ontology or a terminology. Results We obtain fair to moderate interannotator agreement in the practice phase (0.378-0.475. With improved guidelines and additional semantic equivalence criteria, the agreement increases by 12% (0.415 to 0.536 in the main annotation phase. In addition, we find that agreement increases to 0.688 when the agreement calculation is limited to those predications that are based only on the explicitly provided UMLS concepts and relations. Conclusions While interannotator agreement in the practice phase confirms that conceptual annotation is a challenging task, the increasing agreement in the main annotation phase points out that an acceptable level of agreement can be achieved in multiple iterations, by setting stricter guidelines and establishing semantic equivalence criteria. Mapping text to ontological concepts emerges as the main challenge in conceptual annotation. Annotating predications involving biomolecular

  2. [An improved N-FINDR endmember extraction algorithm based on manifold learning and spatial information].

    Science.gov (United States)

    Tang, Xiao-yan; Gao, Kun; Ni, Guo-qiang; Zhu, Zhen-yu; Cheng, Hao-bo

    2013-09-01

    An improved N-FINDR endmember extraction algorithm by combining manifold learning and spatial information is presented under nonlinear mixing assumptions. Firstly, adaptive local tangent space alignment is adapted to seek potential intrinsic low-dimensional structures of hyperspectral high-diemensional data and reduce original data into a low-dimensional space. Secondly, spatial preprocessing is used by enhancing each pixel vector in spatially homogeneous areas, according to the continuity of spatial distribution of the materials. Finally, endmembers are extracted by looking for the largest simplex volume. The proposed method can increase the precision of endmember extraction by solving the nonlinearity of hyperspectral data and taking advantage of spatial information. Experimental results on simulated and real hyperspectral data demonstrate that the proposed approach outperformed the geodesic simplex volume maximization (GSVM), vertex component analysis (VCA) and spatial preprocessing N-FINDR method (SPPNFINDR).

  3. OpenCV-Based Nanomanipulation Information Extraction and the Probe Operation in SEM

    Directory of Open Access Journals (Sweden)

    Dongjie Li

    2015-02-01

    Full Text Available Aimed at the established telenanomanipulation system, the method of extracting location information and the strategies of probe operation were studied in this paper. First, the machine learning algorithm of OpenCV was used to extract location information from SEM images. Thus nanowires and probe in SEM images can be automatically tracked and the region of interest (ROI can be marked quickly. Then the location of nanowire and probe can be extracted from the ROI. To study the probe operation strategy, the Van der Waals force between probe and a nanowire was computed; thus relevant operating parameters can be obtained. With these operating parameters, the nanowire in 3D virtual environment can be preoperated and an optimal path of the probe can be obtained. The actual probe runs automatically under the telenanomanipulation system's control. Finally, experiments were carried out to verify the above methods, and results show the designed methods have achieved the expected effect.

  4. Extraction and Network Sharing of Forest Vegetation Information based on SVM

    Directory of Open Access Journals (Sweden)

    Zhang Hannv

    2013-05-01

    Full Text Available The support vector machine (SVM is a new method of data mining, which can deal with regression problems (time series analysis, pattern recognition (classification, discriminant analysis and many other issues very well. In recent years, SVM has been widely used in computer classification and recognition of remote sensing images. This paper is based on Landsat TM image data, using a classification method which is based on support vector machine to extract the forest cover information of Dahuanggou tree farm of Changbai Mountain area, and compare with the conventional maximum likelihood classification. The results show that extraction accuracy of forest information based on support vector machine, Kappa values are 0.9810, 0.9716, 0.9753, which are exceeding the extraction accuracy of maximum likelihood method (MLC and Kappa value of 0.9634, the method has good maneuverability and practicality.

  5. A method of building information extraction based on mathematical morphology and multiscale

    Science.gov (United States)

    Li, Jing-wen; Wang, Ke; Zhang, Zi-ping; Xue, Long-li; Yin, Shou-qiang; Zhou, Song

    2015-12-01

    In view of monitoring the changes of buildings on Earth's surface ,by analyzing the distribution characteristics of building in remote sensing image, combined with multi-scale in image segmentation and the advantages of mathematical morphology, this paper proposes a multi-scale combined with mathematical morphology of high resolution remote sensing image segmentation method, and uses the multiple fuzzy classification method and the shadow of auxiliary method to extract information building, With the comparison of k-means classification, and the traditional maximum likelihood classification method, the results of experiment object based on multi-scale combined with mathematical morphology of image segmentation and extraction method, can accurately extract the structure of the information is more clear classification data, provide the basis for the intelligent monitoring of earth data and theoretical support.

  6. Information retrieval and terminology extraction in online resources for patients with diabetes.

    Science.gov (United States)

    Seljan, Sanja; Baretić, Maja; Kucis, Vlasta

    2014-06-01

    Terminology use, as a mean for information retrieval or document indexing, plays an important role in health literacy. Specific types of users, i.e. patients with diabetes need access to various online resources (on foreign and/or native language) searching for information on self-education of basic diabetic knowledge, on self-care activities regarding importance of dietetic food, medications, physical exercises and on self-management of insulin pumps. Automatic extraction of corpus-based terminology from online texts, manuals or professional papers, can help in building terminology lists or list of "browsing phrases" useful in information retrieval or in document indexing. Specific terminology lists represent an intermediate step between free text search and controlled vocabulary, between user's demands and existing online resources in native and foreign language. The research aiming to detect the role of terminology in online resources, is conducted on English and Croatian manuals and Croatian online texts, and divided into three interrelated parts: i) comparison of professional and popular terminology use ii) evaluation of automatic statistically-based terminology extraction on English and Croatian texts iii) comparison and evaluation of extracted terminology performed on English manual using statistical and hybrid approaches. Extracted terminology candidates are evaluated by comparison with three types of reference lists: list created by professional medical person, list of highly professional vocabulary contained in MeSH and list created by non-medical persons, made as intersection of 15 lists. Results report on use of popular and professional terminology in online diabetes resources, on evaluation of automatically extracted terminology candidates in English and Croatian texts and on comparison of statistical and hybrid extraction methods in English text. Evaluation of automatic and semi-automatic terminology extraction methods is performed by recall

  7. Information extraction with object based support vector machines and vegetation indices

    Science.gov (United States)

    Ustuner, Mustafa; Abdikan, Saygin; Balik Sanli, Fusun

    2016-07-01

    Information extraction through remote sensing data is important for policy and decision makers as extracted information provide base layers for many application of real world. Classification of remotely sensed data is the one of the most common methods of extracting information however it is still a challenging issue because several factors are affecting the accuracy of the classification. Resolution of the imagery, number and homogeneity of land cover classes, purity of training data and characteristic of adopted classifiers are just some of these challenging factors. Object based image classification has some superiority than pixel based classification for high resolution images since it uses geometry and structure information besides spectral information. Vegetation indices are also commonly used for the classification process since it provides additional spectral information for vegetation, forestry and agricultural areas. In this study, the impacts of the Normalized Difference Vegetation Index (NDVI) and Normalized Difference Red Edge Index (NDRE) on the classification accuracy of RapidEye imagery were investigated. Object based Support Vector Machines were implemented for the classification of crop types for the study area located in Aegean region of Turkey. Results demonstrated that the incorporation of NDRE increase the classification accuracy from 79,96% to 86,80% as overall accuracy, however NDVI decrease the classification accuracy from 79,96% to 78,90%. Moreover it is proven than object based classification with RapidEye data give promising results for crop type mapping and analysis.

  8. An Information Extraction Core System for Real World German Text Processing

    CERN Document Server

    Neumann, G; Baur, J; Becker, M; Braun, C

    1997-01-01

    This paper describes SMES, an information extraction core system for real world German text processing. The basic design criterion of the system is of providing a set of basic powerful, robust, and efficient natural language components and generic linguistic knowledge sources which can easily be customized for processing different tasks in a flexible manner.

  9. Web信息抽取系统的设计%Design of Web Information Extraction System

    Institute of Scientific and Technical Information of China (English)

    刘斌; 张晓婧

    2013-01-01

    In order to obtain the scattered information hidden in Web pages,Web information extraction system design.The system first uses a modified HITS algorithm for topic selection information collection; then the Web page's HTML document structure of the data pre-processing; Finally,based on the XPath DOM tree generation algorithm to obtain the absolute path is an XPath node marked expression,and use the XPath language with XSLT technology to write extraction rules,resulting in a structured database or XML file,to achieve the positioning and Web information extraction.Extraction through a shopping site experiments show that the extraction system works well,can achieve similar batch extract Web page.%为了获取分散Web页面中隐含信息,设计了Web信息抽取系统.该系统首先使用一种改进的HITS主题精选算法进行信息采集;然后对Web页面的HTML结构进行文档的数据预处理;最后,基于DOM树的XPath绝对路径生成算法来获取被标注结点的XPath表达式,并使用XPath语言结合XSLT技术来编写抽取规则,从而得到结构化的数据库或XML文件,实现了Web信息的定位和抽取.通过一个购物网站的抽取实验证明,该系统的抽取效果良好,可以实现相似Web页面的批量抽取.

  10. Identifying and extracting patient smoking status information from clinical narrative texts in Spanish.

    Science.gov (United States)

    Figueroa, Rosa L; Soto, Diego A; Pino, Esteban J

    2014-01-01

    In this work we present a system to identify and extract patient's smoking status from clinical narrative text in Spanish. The clinical narrative text was processed using natural language processing techniques, and annotated by four people with a biomedical background. The dataset used for classification had 2,465 documents, each one annotated with one of the four smoking status categories. We used two feature representations: single word token and bigrams. The classification problem was divided in two levels. First recognizing between smoker (S) and non-smoker (NS); second recognizing between current smoker (CS) and past smoker (PS). For each feature representation and classification level, we used two classifiers: Support Vector Machines (SVM) and Bayesian Networks (BN). We split our dataset as follows: a training set containing 66% of the available documents that was used to build classifiers and a test set containing the remaining 34% of the documents that was used to test and evaluate the model. Our results show that SVM together with the bigram representation performed better in both classification levels. For S vs NS classification level performance measures were: ACC=85%, Precision=85%, and Recall=90%. For CS vs PS classification level performance measures were: ACC=87%, Precision=91%, and Recall=94%.

  11. Applications of computational intelligence in biomedical technology

    CERN Document Server

    Majernik, Jaroslav; Pancerz, Krzysztof; Zaitseva, Elena

    2016-01-01

    This book presents latest results and selected applications of Computational Intelligence in Biomedical Technologies. Most of contributions deal with problems of Biomedical and Medical Informatics, ranging from theoretical considerations to practical applications. Various aspects of development methods and algorithms in Biomedical and Medical Informatics as well as Algorithms for medical image processing, modeling methods are discussed. Individual contributions also cover medical decision making support, estimation of risks of treatments, reliability of medical systems, problems of practical clinical applications and many other topics  This book is intended for scientists interested in problems of Biomedical Technologies, for researchers and academic staff, for all dealing with Biomedical and Medical Informatics, as well as PhD students. Useful information is offered also to IT companies, developers of equipment and/or software for medicine and medical professionals.  .

  12. Question Processing and Clustering in INDOC: A Biomedical Question Answering System

    Directory of Open Access Journals (Sweden)

    Ankush Mittal

    2007-12-01

    Full Text Available The exponential growth in the volume of publications in the biomedical domain has made it impossible for an individual to keep pace with the advances. Even though evidence-based medicine has gained wide acceptance, the physicians are unable to access the relevant information in the required time, leaving most of the questions unanswered. This accentuates the need for fast and accurate biomedical question answering systems. In this paper we introduce INDOC—a biomedical question answering system based on novel ideas of indexing and extracting the answer to the questions posed. INDOC displays the results in clusters to help the user arrive the most relevant set of documents quickly. Evaluation was done against the standard OHSUMED test collection. Our system achieves high accuracy and minimizes user effort.

  13. Framework for automatic information extraction from research papers on nanocrystal devices

    Directory of Open Access Journals (Sweden)

    Thaer M. Dieb

    2015-09-01

    Full Text Available To support nanocrystal device development, we have been working on a computational framework to utilize information in research papers on nanocrystal devices. We developed an annotated corpus called “ NaDev” (Nanocrystal Device Development for this purpose. We also proposed an automatic information extraction system called “NaDevEx” (Nanocrystal Device Automatic Information Extraction Framework. NaDevEx aims at extracting information from research papers on nanocrystal devices using the NaDev corpus and machine-learning techniques. However, the characteristics of NaDevEx were not examined in detail. In this paper, we conduct system evaluation experiments for NaDevEx using the NaDev corpus. We discuss three main issues: system performance, compared with human annotators; the effect of paper type (synthesis or characterization on system performance; and the effects of domain knowledge features (e.g., a chemical named entity recognition system and list of names of physical quantities on system performance. We found that overall system performance was 89% in precision and 69% in recall. If we consider identification of terms that intersect with correct terms for the same information category as the correct identification, i.e., loose agreement (in many cases, we can find that appropriate head nouns such as temperature or pressure loosely match between two terms, the overall performance is 95% in precision and 74% in recall. The system performance is almost comparable with results of human annotators for information categories with rich domain knowledge information (source material. However, for other information categories, given the relatively large number of terms that exist only in one paper, recall of individual information categories is not high (39–73%; however, precision is better (75–97%. The average performance for synthesis papers is better than that for characterization papers because of the lack of training examples for

  14. Framework for automatic information extraction from research papers on nanocrystal devices.

    Science.gov (United States)

    Dieb, Thaer M; Yoshioka, Masaharu; Hara, Shinjiro; Newton, Marcus C

    2015-01-01

    To support nanocrystal device development, we have been working on a computational framework to utilize information in research papers on nanocrystal devices. We developed an annotated corpus called " NaDev" (Nanocrystal Device Development) for this purpose. We also proposed an automatic information extraction system called "NaDevEx" (Nanocrystal Device Automatic Information Extraction Framework). NaDevEx aims at extracting information from research papers on nanocrystal devices using the NaDev corpus and machine-learning techniques. However, the characteristics of NaDevEx were not examined in detail. In this paper, we conduct system evaluation experiments for NaDevEx using the NaDev corpus. We discuss three main issues: system performance, compared with human annotators; the effect of paper type (synthesis or characterization) on system performance; and the effects of domain knowledge features (e.g., a chemical named entity recognition system and list of names of physical quantities) on system performance. We found that overall system performance was 89% in precision and 69% in recall. If we consider identification of terms that intersect with correct terms for the same information category as the correct identification, i.e., loose agreement (in many cases, we can find that appropriate head nouns such as temperature or pressure loosely match between two terms), the overall performance is 95% in precision and 74% in recall. The system performance is almost comparable with results of human annotators for information categories with rich domain knowledge information (source material). However, for other information categories, given the relatively large number of terms that exist only in one paper, recall of individual information categories is not high (39-73%); however, precision is better (75-97%). The average performance for synthesis papers is better than that for characterization papers because of the lack of training examples for characterization papers

  15. A Framework For Extracting Information From Web Using VTD-XML‘s XPath

    Directory of Open Access Journals (Sweden)

    C. Subhashini

    2012-03-01

    Full Text Available The exponential growth of WWW (World Wide Web is the cause for vast pool of information as well as several challenges posed by it, such as extracting potentially useful and unknown information from WWW. Many websites are built with HTML, because of its unstructured layout, it is difficult to obtain effective and precise data from web using HTML. The advent of XML (Extensible Markup Language proposes a better solution to extract useful knowledge from WWW. Web Data Extraction based on XML Technology solves this problem because XML is a general purpose specification for exchanging data over the Web. In this paper, a framework is suggested to extract the data from the web.Here the semi-structured data in the web page is transformed into well-structured data using standard XML technologies and the new parsing technique called extended VTD-XML (Virtual Token Descriptorfor XML along with Xpath implementation has been used to extract data from the well-structured XML document.

  16. Information Extraction for System-Software Safety Analysis: Calendar Year 2008 Year-End Report

    Science.gov (United States)

    Malin, Jane T.

    2009-01-01

    This annual report describes work to integrate a set of tools to support early model-based analysis of failures and hazards due to system-software interactions. The tools perform and assist analysts in the following tasks: 1) extract model parts from text for architecture and safety/hazard models; 2) combine the parts with library information to develop the models for visualization and analysis; 3) perform graph analysis and simulation to identify and evaluate possible paths from hazard sources to vulnerable entities and functions, in nominal and anomalous system-software configurations and scenarios; and 4) identify resulting candidate scenarios for software integration testing. There has been significant technical progress in model extraction from Orion program text sources, architecture model derivation (components and connections) and documentation of extraction sources. Models have been derived from Internal Interface Requirements Documents (IIRDs) and FMEA documents. Linguistic text processing is used to extract model parts and relationships, and the Aerospace Ontology also aids automated model development from the extracted information. Visualizations of these models assist analysts in requirements overview and in checking consistency and completeness.

  17. Clinic expert information extraction based on domain model and block importance model.

    Science.gov (United States)

    Zhang, Yuanpeng; Wang, Li; Qian, Danmin; Geng, Xingyun; Yao, Dengfu; Dong, Jiancheng

    2015-11-01

    To extract expert clinic information from the Deep Web, there are two challenges to face. The first one is to make a judgment on forms. A novel method based on a domain model, which is a tree structure constructed by the attributes of query interfaces is proposed. With this model, query interfaces can be classified to a domain and filled in with domain keywords. Another challenge is to extract information from response Web pages indexed by query interfaces. To filter the noisy information on a Web page, a block importance model is proposed, both content and spatial features are taken into account in this model. The experimental results indicate that the domain model yields a precision 4.89% higher than that of the rule-based method, whereas the block importance model yields an F1 measure 10.5% higher than that of the XPath method.

  18. Drug name recognition in biomedical texts: a machine-learning-based method.

    Science.gov (United States)

    He, Linna; Yang, Zhihao; Lin, Hongfei; Li, Yanpeng

    2014-05-01

    Currently, there is an urgent need to develop a technology for extracting drug information automatically from biomedical texts, and drug name recognition is an essential prerequisite for extracting drug information. This article presents a machine-learning-based approach to recognize drug names in biomedical texts. In this approach, a drug name dictionary is first constructed with the external resource of DrugBank and PubMed. Then a semi-supervised learning method, feature coupling generalization, is used to filter this dictionary. Finally, the dictionary look-up and the condition random field method are combined to recognize drug names. Experimental results show that our approach achieves an F-score of 92.54% on the test set of DDIExtraction2011.

  19. Extraction of spatial information from remotely sensed image data - an example: gloria sidescan sonar images

    Science.gov (United States)

    Chavez, Pat S.; Gardner, James V.

    1994-01-01

    A method to extract spatial amplitude and variability information from remotely sensed digital imaging data is presented. High Pass Filters (HPFs) are used to compute both a Spatial Amplitude Image/Index (SAI) and Spatial Variability Image/Index (SVI) at the local, intermediate, and regional scales. Used as input to principal component analysis and automatic clustering classification, the results indicate that spatial information at scales other than local is useful in the analysis of remotely sensed data. The resultant multi-spatial data set allows the user to study and analyze an image based more on the complete spatial characteristics of an image than only local textural information.

  20. Extraction of Hidden Social Networks from Wiki-Environment Involved in Information Conflict

    Directory of Open Access Journals (Sweden)

    Rasim M. Alguliyev

    2016-03-01

    Full Text Available Social network analysis is a widely used technique to analyze relationships among wiki-users in Wikipedia. In this paper the method to identify hidden social networks participating in information conflicts in wiki-environment is proposed. In particular, we describe how text clustering techniques can be used for extraction of hidden social networks of wiki-users caused information conflict. By clustering unstructured text articles caused information conflict we create social network of wiki-users. For clustering of the conflict articles a hybrid weighted fuzzy-c-means method is proposed.

  1. Autoradiography: Biomedical applications. January, 1975-August, 1981 (citations from the International Information Service for the Physics and Engineering Communities Data Base). Report for January 75-August 81

    Energy Technology Data Exchange (ETDEWEB)

    1981-08-01

    This bibliography contains citations concerning the methods, equipment, and biomedical applications of autoradiography. Electron microscopy (EM) is discussed at length, and sample preparation for EM is detailed. Numerous biological, biochemical and biophysical studies are discussed. (Contains 84 citations fully indexed and including a title list.)

  2. A theoretical extraction scheme of transport information based on exclusion models

    Institute of Scientific and Technical Information of China (English)

    Chen Hua; Du Lei; Qu Cheng-Li; Li Wei-Hua; He Liang; Chen Wen-Hao; Sun Peng

    2010-01-01

    In order to explore how to extract more transport information from current fluctuation, a theoretical extraction scheme is presented in a single barrier structure based on exclusion models, which include counter-flows model and tunnel model. The first four cumulants of these two exclusion models are computed in a single barrier structure, and their characteristics are obtained. A scheme with the help of the first three cumulants is devised to check a transport process to follow the counter-flows model, the tunnel model or neither of them. Time series generated by Monte Carlo techniques is adopted to validate the abstraction procedure, and the result is reasonable.

  3. Orchard spatial information extraction from SPOT-5 image based on CART model

    Science.gov (United States)

    Li, Deyi; Zhang, Shuwen

    2009-07-01

    Orchard is an important agricultural industry and typical land use type in Shandong peninsula of China. This article focused on the automatic information extraction of orchard using SPOT-5 image. After analyzing every object's spectrum, we proposed a CART model based on sub-region and hierarchy theory by exploring spectrum, texture and topography attributes. The whole area was divided into coastal plain region and hill region based on SRTM data and extracted respectively. The accuracy reached to 86.40%, which was much higher than supervised classification method.

  4. Extracting directed information flow networks: an application to genetics and semantics

    CERN Document Server

    Masucci, A P; Hernández-García, E; Kalampokis, A

    2010-01-01

    We introduce a general method to infer the directional information flow between populations whose elements are described by n-dimensional vectors of symbolic attributes. The method is based on the Jensen-Shannon divergence and on the Shannon entropy and has a wide range of application. We show here the results of two applications: first extracting the network of genetic flow between the meadows of the seagrass Poseidonia Oceanica, where the meadow elements are specified by sets of microsatellite markers, then we extract the semantic flow network from a set of Wikipedia pages, showing the semantic channels between different areas of knowledge.

  5. Textural Properties of Hybrid Biomedical Materials Made from Extracts of Tournefortia hirsutissima L. Imbibed and Deposited on Mesoporous and Microporous Materials

    Directory of Open Access Journals (Sweden)

    Miguel Ángel Hernández

    2016-01-01

    Full Text Available Our research group has developed a group of hybrid biomedical materials potentially useful in the healing of diabetic foot ulcerations. The organic part of this type of hybrid materials consists of nanometric deposits, proceeding from the Mexican medicinal plant Tournefortia hirsutissima L., while the inorganic part is composed of a zeolite mixture that includes LTA, ZSM-5, clinoptilolite, and montmorillonite (PZX as well as a composite material, made of CaCO3 and montmorillonite (NABE. The organic part has been analyzed by GC-MS to detect the most abundant components present therein. In turn, the inorganic supports were characterized by XRD, SEM, and High Resolution Adsorption (HRADS of N2 at 76 K. Through this latter methodology, the external surface area of the hybrid materials was evaluated; besides, the most representative textural properties of each substrate such as total pore volume, pore size distribution, and, in some cases, the volume of micropores were calculated. The formation and stabilization of nanodeposits on the inorganic segments of the hybrid supports led to a partial blockage of the microporosity of the LTA and ZSM5 zeolites; this same effect occurred with the NABE and PZX substrates.

  6. Surface tailoring of inorganic materials for biomedical applications

    CERN Document Server

    Rimondini, Lia; Vernè, Enrica

    2012-01-01

    This e-book provides comprehensive information on technologies for development and characterization of successful functionalized materials for biomedical applications relevant to surface modification.

  7. Extraction of palaeochannei information from remote sensing imagery in the east of Chaohu Lake, China

    Institute of Scientific and Technical Information of China (English)

    Xinyuan WANG; Zhenya GUO; Li WU; Cheng ZHU; Hui HE

    2012-01-01

    Palaeochannels are deposits of unconsolidated sediments or semi-consolidated sedimentary rocks deposited in ancient,currently inactive fiver and stream channel systems.It is distinct from the overbank deposits of currently active river channels,including ephemeral water courses which do not regularly flow.We have introduced a spectral characteristics-based palaeochannel information extraction model from SPOT-5 imagery with special time phase,which has been built by virtue of an analysis of remote sensing mechanism and spectral characteristics of the palaeochannel,combined with its distinction from the spatial distribution and spectral features of currently active river channels,also with the establishment of remote sensing judging features of the palaeochannel in remote sensing image.This model follows the process of supervised classification → farmland masking and primary component analysis → underground palaeochannel information extractioninformation combination → palaeochannel system image.The Zhegao River Valley in the east of Chaohu Lake was selected as a study area,and SPOT-5 imagery was used as a source of data.The result was satisfactory when this method has been successfully applied to extract the palaeochannel information,which can provide good reference for regional remote sensing archeology and neotectonic research.However,the applicability of this method needs to be tested further in other areas as the spatial characteristics and spectral response of palaeochannel might be different.

  8. A study of extraction of petal region on flower picture using HSV color information

    Science.gov (United States)

    Yanagihara, Yoshio; Nakayama, Ryo

    2014-01-01

    It is one of useful and interesting applications to discriminate the kind of the flower or recognize the name of the flower, as example of retrieving flower database. As its contour line of the petal region of flower is useful for such problems, it is important to extract the precise region of the petal of a flower picture. In this paper, the method which extracts petal regions on a flower picture using HSV color information is proposed, such to discriminate the kind of the flower. The experiments show that the proposed method can extract petal regions at the success rate of about 90%, which is thought to be satisfied. In detail, the success rates of one-colored flower, plural-colored flower, and white flower are about 98%, 85%, and 83%, respectively.

  9. Biomedical Engineering Laboratory

    Science.gov (United States)

    2007-11-02

    The Masters of Engineering program with concentration in Biomedical Engineering at Tennessee State University was established in fall 2000. Under... biomedical engineering . The lab is fully equipped with 10 Pentium5-based, 2 Pentium4-based laptops for mobile experiments at remote locations, 8 Biopac...students (prospective graduate students in biomedical engineering ) are regularly using this lab. This summer, 8 new prospective graduate students

  10. Web Page Information Extraction Technology%网页信息提取技术

    Institute of Scientific and Technical Information of China (English)

    邵振凯

    2013-01-01

    With the rapid development of the Internet,the amount of information in the Web page has become very large,how to quickly and efficiently search and find valuable information has become an important aspect of Web research. In this regard a tag extraction meth-od is proposed. Optimize the Web page into good HTML format documents with JTidy,and resolve to a DOM tree. Then use tag extrac-tion approach to extract the tags contain the text message content from DOM tree,remove the tags used to control the Web interaction and display,and use the method based on the punctuation information extraction method to remove the copyright notice and other informa-tion. The results on a number of different sites extraction show that the tags extraction methods not only have a great generality but also can accurately extract site theme.%随着互联网的快速发展,Web页面上的信息量已变得非常巨大,面对网页上海量的信息资源,如何快速有效地检索及发现有价值的信息已成为Web研究的一个重要方面。对此提出了一种标签提取方法。利用JTidy将网页优化为格式良好的HTML文档并解析为DOM树,然后用标签提取方法对该DOM树中包含有文本信息内容的叶子节点标签进行提取,把用于控制网页交互性和显示的标签删除掉,并运用基于标点符号的信息提取方法去除版权说明等信息。对不同网站的网页进行抽取实验,结果表明标签提取方法不但通用性强,而且能够准确地提取网页的主题信息。

  11. Biomedical engineering principles

    CERN Document Server

    Ritter, Arthur B; Valdevit, Antonio; Ascione, Alfred N

    2011-01-01

    Introduction: Modeling of Physiological ProcessesCell Physiology and TransportPrinciples and Biomedical Applications of HemodynamicsA Systems Approach to PhysiologyThe Cardiovascular SystemBiomedical Signal ProcessingSignal Acquisition and ProcessingTechniques for Physiological Signal ProcessingExamples of Physiological Signal ProcessingPrinciples of BiomechanicsPractical Applications of BiomechanicsBiomaterialsPrinciples of Biomedical Capstone DesignUnmet Clinical NeedsEntrepreneurship: Reasons why Most Good Designs Never Get to MarketAn Engineering Solution in Search of a Biomedical Problem

  12. Fundamental of biomedical engineering

    CERN Document Server

    Sawhney, GS

    2007-01-01

    About the Book: A well set out textbook explains the fundamentals of biomedical engineering in the areas of biomechanics, biofluid flow, biomaterials, bioinstrumentation and use of computing in biomedical engineering. All these subjects form a basic part of an engineer''s education. The text is admirably suited to meet the needs of the students of mechanical engineering, opting for the elective of Biomedical Engineering. Coverage of bioinstrumentation, biomaterials and computing for biomedical engineers can meet the needs of the students of Electronic & Communication, Electronic & Instrumenta

  13. International symposium on Biomedical Data Infrastructure (BDI 2013)

    CERN Document Server

    Dhillon, Sarinder; Advances in biomedical infrastructure 2013

    2013-01-01

    Current Biomedical Databases are independently administered in geographically distinct locations, lending them almost ideally to adoption of intelligent data management approaches. This book focuses on research issues, problems and opportunities in Biomedical Data Infrastructure identifying new issues and directions for future research in Biomedical Data and Information Retrieval, Semantics in Biomedicine, and Biomedical Data Modeling and Analysis. The book will be a useful guide for researchers, practitioners, and graduate-level students interested in learning state-of-the-art development in biomedical data management.

  14. Multilevel spatial semantic model for urban house information extraction automatically from QuickBird imagery

    Science.gov (United States)

    Guan, Li; Wang, Ping; Liu, Xiangnan

    2006-10-01

    Based on the introduction to the characters and constructing flow of space semantic model, the feature space and context of house information in high resolution remote sensing image are analyzed, and the house semantic network model of Quick Bird image is also constructed. Furthermore, the accuracy and practicability of space semantic model are checked up through extracting house information automatically from Quick Bird image after extracting candidate semantic nodes to the image by taking advantage of grey division method, window threshold value method and Hough transformation. Sample result indicates that its type coherence, shape coherence and area coherence are 96.75%, 89.5 % and 88 % respectively. Thereinto the effect of the extraction of the houses with rectangular roof is the best and that with herringbone and the polygonal roofs is just ideal. However, the effect of the extraction of the houses with round roof is not satisfied and thus they need the further perfection to the semantic model to make them own higher applied value.

  15. Extraction of Remote Sensing Information Ofbanana Under Support of 3S Technology Inguangxi Province

    Science.gov (United States)

    Yang, Xin; Sun, Han; Tan, Zongkun; Ding, Meihua

    This paper presents an automatic approach to planting areas extraction for mixed vegetation and hilly region, more cloud using moderate spatial resolution and high temporal resolution MODIS data around Guangxi province, south of China. According to banana growth lasting more 9 to 11 months, and the areas are reduced during crush season, the Maximum likelihood was used to extract the information of banana planting and their spatial distribution through the calculation of multiple-phase MODIS-NDVI in Guangxi and stylebook training regions of banana of being selected by GPS. Compared with the large and little regions of banana planting in monitoring image and the investigation of on the spot with GPS, the resolute shows that the banana planting information in remote sensing image are true. In this research, multiple-phase MODIS data were received during banana main growing season and preprocessed; NDVI temporal profiles of banana were generated;models for planting areas extraction were developed based on the analysis of temporal NDVI curves; and spatial distribution map of planting areas of banana in Guangxi in 2006 were created. The study suggeststhat it is possible to extract planting areas automatically from MODIS data for large areas.

  16. An Useful Information Extraction using Image Mining Techniques from Remotely Sensed Image (RSI

    Directory of Open Access Journals (Sweden)

    Dr. C. Jothi Venkateswaran,

    2010-11-01

    Full Text Available Information extraction using mining techniques from remote sensing image (RSI is rapidly gaining attention among researchers and decision makers because of its potential in application oriented studies. Knowledge discovery from image poses many interesting challenges such as preprocessing the image data set, training the data and discovering useful image patterns applicable to many newapplication frontiers. In the image rich domain of RSI, image mining implies the synergy of data mining and image processing technology. Such culmination of techniques renders a valuable tool in information extraction. Also, this encompasses the problem of handling a larger data base of varied image data formats representing various levels ofinformation such as pixel, local and regional. In the present paper, various preprocessing corrections and techniques of image mining are discussed.

  17. The BioLexicon: a large-scale terminological resource for biomedical text mining

    Directory of Open Access Journals (Sweden)

    Thompson Paul

    2011-10-01

    Full Text Available Abstract Background Due to the rapidly expanding body of biomedical literature, biologists require increasingly sophisticated and efficient systems to help them to search for relevant information. Such systems should account for the multiple written variants used to represent biomedical concepts, and allow the user to search for specific pieces of knowledge (or events involving these concepts, e.g., protein-protein interactions. Such functionality requires access to detailed information about words used in the biomedical literature. Existing databases and ontologies often have a specific focus and are oriented towards human use. Consequently, biological knowledge is dispersed amongst many resources, which often do not attempt to account for the large and frequently changing set of variants that appear in the literature. Additionally, such resources typically do not provide information about how terms relate to each other in texts to describe events. Results This article provides an overview of the design, construction and evaluation of a large-scale lexical and conceptual resource for the biomedical domain, the BioLexicon. The resource can be exploited by text mining tools at several levels, e.g., part-of-speech tagging, recognition of biomedical entities, and the extraction of events in which they are involved. As such, the BioLexicon must account for real usage of words in biomedical texts. In particular, the BioLexicon gathers together different types of terms from several existing data resources into a single, unified repository, and augments them with new term variants automatically extracted from biomedical literature. Extraction of events is facilitated through the inclusion of biologically pertinent verbs (around which events are typically organized together with information about typical patterns of grammatical and semantic behaviour, which are acquired from domain-specific texts. In order to foster interoperability, the BioLexicon is

  18. Monadic datalog and the expressive power of languages for Web information extraction

    OpenAIRE

    Gottlob, Georg; Koch, Christoph

    2004-01-01

    Research on information extraction from Web pages (wrapping) has seen much activity recently (particularly systems implementations), but little work has been done on formally studying the expressiveness of the formalisms proposed or on the theoretical foundations of wrapping. In this paper, we first study monadic datalog over trees as a wrapping language. We show that this simple language is equivalent to monadic second order logic (MSO) in its ability to specify wrappers. We believe that MSO...

  19. An Useful Information Extraction using Image Mining Techniques from Remotely Sensed Image (RSI)

    OpenAIRE

    Dr. C. Jothi Venkateswaran,; Murugan, S.; Dr. N. Radhakrishnan

    2010-01-01

    Information extraction using mining techniques from remote sensing image (RSI) is rapidly gaining attention among researchers and decision makers because of its potential in application oriented studies. Knowledge discovery from image poses many interesting challenges such as preprocessing the image data set, training the data and discovering useful image patterns applicable to many newapplication frontiers. In the image rich domain of RSI, image mining implies the synergy of data mining and ...

  20. Road Extraction from High-resolution Remote Sensing Images Based on Multiple Information Fusion

    Directory of Open Access Journals (Sweden)

    LI Xiao-feng

    2016-02-01

    Full Text Available Road extraction from high-resolution remote sensing images has been considered to be a significant but very difficult task.Especially the spectrum of some buildings is similar with that of roads,which makes the surfaces being connect with each other after classification and difficult to be distinguished.Based on the cooperation between road surfaces and edges,this paper presents an approach to purify roads from high-resolution remote sensing images.Firstly,we try to improve the extraction accuracy of road surfaces and edges respectively.The logic cooperation between these two binary images is used to separate road and non-road objects.Then the road objects are confirmed by the cooperation between surfaces and edges.And the effective shape indices(e.g.polar moment of inertia and narrow extent index are applied to eliminate non-road objects.So the road information is refined.The experiments indicate that the proposed approach is efficient for eliminating non-road information and extracting road information from high-resolution remote sensing image.

  1. Biomedical signal and image processing

    CERN Document Server

    Najarian, Kayvan

    2012-01-01

    INTRODUCTION TO DIGITAL SIGNAL AND IMAGE PROCESSINGSignals and Biomedical Signal ProcessingIntroduction and OverviewWhat is a ""Signal""?Analog, Discrete, and Digital SignalsProcessing and Transformation of SignalsSignal Processing for Feature ExtractionSome Characteristics of Digital ImagesSummaryProblemsFourier TransformIntroduction and OverviewOne-Dimensional Continuous Fourier TransformSampling and NYQUIST RateOne-Dimensional Discrete Fourier TransformTwo-Dimensional Discrete Fourier TransformFilter DesignSummaryProblemsImage Filtering, Enhancement, and RestorationIntroduction and Overview

  2. The Ontology for Biomedical Investigations.

    Science.gov (United States)

    Bandrowski, Anita; Brinkman, Ryan; Brochhausen, Mathias; Brush, Matthew H; Bug, Bill; Chibucos, Marcus C; Clancy, Kevin; Courtot, Mélanie; Derom, Dirk; Dumontier, Michel; Fan, Liju; Fostel, Jennifer; Fragoso, Gilberto; Gibson, Frank; Gonzalez-Beltran, Alejandra; Haendel, Melissa A; He, Yongqun; Heiskanen, Mervi; Hernandez-Boussard, Tina; Jensen, Mark; Lin, Yu; Lister, Allyson L; Lord, Phillip; Malone, James; Manduchi, Elisabetta; McGee, Monnie; Morrison, Norman; Overton, James A; Parkinson, Helen; Peters, Bjoern; Rocca-Serra, Philippe; Ruttenberg, Alan; Sansone, Susanna-Assunta; Scheuermann, Richard H; Schober, Daniel; Smith, Barry; Soldatova, Larisa N; Stoeckert, Christian J; Taylor, Chris F; Torniai, Carlo; Turner, Jessica A; Vita, Randi; Whetzel, Patricia L; Zheng, Jie

    2016-01-01

    The Ontology for Biomedical Investigations (OBI) is an ontology that provides terms with precisely defined meanings to describe all aspects of how investigations in the biological and medical domains are conducted. OBI re-uses ontologies that provide a representation of biomedical knowledge from the Open Biological and Biomedical Ontologies (OBO) project and adds the ability to describe how this knowledge was derived. We here describe the state of OBI and several applications that are using it, such as adding semantic expressivity to existing databases, building data entry forms, and enabling interoperability between knowledge resources. OBI covers all phases of the investigation process, such as planning, execution and reporting. It represents information and material entities that participate in these processes, as well as roles and functions. Prior to OBI, it was not possible to use a single internally consistent resource that could be applied to multiple types of experiments for these applications. OBI has made this possible by creating terms for entities involved in biological and medical investigations and by importing parts of other biomedical ontologies such as GO, Chemical Entities of Biological Interest (ChEBI) and Phenotype Attribute and Trait Ontology (PATO) without altering their meaning. OBI is being used in a wide range of projects covering genomics, multi-omics, immunology, and catalogs of services. OBI has also spawned other ontologies (Information Artifact Ontology) and methods for importing parts of ontologies (Minimum information to reference an external ontology term (MIREOT)). The OBI project is an open cross-disciplinary collaborative effort, encompassing multiple research communities from around the globe. To date, OBI has created 2366 classes and 40 relations along with textual and formal definitions. The OBI Consortium maintains a web resource (http://obi-ontology.org) providing details on the people, policies, and issues being addressed

  3. Education of biomedical engineering in Taiwan.

    Science.gov (United States)

    Lin, Kang-Ping; Kao, Tsair; Wang, Jia-Jung; Chen, Mei-Jung; Su, Fong-Chin

    2014-01-01

    Biomedical Engineers (BME) play an important role in medical and healthcare society. Well educational programs are important to support the healthcare systems including hospitals, long term care organizations, manufacture industries of medical devices/instrumentations/systems, and sales/services companies of medical devices/instrumentations/system. In past 30 more years, biomedical engineering society has accumulated thousands people hold a biomedical engineering degree, and work as a biomedical engineer in Taiwan. Most of BME students can be trained in biomedical engineering departments with at least one of specialties in bioelectronics, bio-information, biomaterials or biomechanics. Students are required to have internship trainings in related institutions out of campus for 320 hours before graduating. Almost all the biomedical engineering departments are certified by IEET (Institute of Engineering Education Taiwan), and met the IEET requirement in which required mathematics and fundamental engineering courses. For BMEs after graduation, Taiwanese Society of Biomedical Engineering (TSBME) provides many continue-learning programs and certificates for all members who expect to hold the certification as a professional credit in his working place. In current status, many engineering departments in university are continuously asked to provide joint programs with BME department to train much better quality students. BME is one of growing fields in Taiwan.

  4. Evaluation of research in biomedical ontologies.

    Science.gov (United States)

    Hoehndorf, Robert; Dumontier, Michel; Gkoutos, Georgios V

    2013-11-01

    Ontologies are now pervasive in biomedicine, where they serve as a means to standardize terminology, to enable access to domain knowledge, to verify data consistency and to facilitate integrative analyses over heterogeneous biomedical data. For this purpose, research on biomedical ontologies applies theories and methods from diverse disciplines such as information management, knowledge representation, cognitive science, linguistics and philosophy. Depending on the desired applications in which ontologies are being applied, the evaluation of research in biomedical ontologies must follow different strategies. Here, we provide a classification of research problems in which ontologies are being applied, focusing on the use of ontologies in basic and translational research, and we demonstrate how research results in biomedical ontologies can be evaluated. The evaluation strategies depend on the desired application and measure the success of using an ontology for a particular biomedical problem. For many applications, the success can be quantified, thereby facilitating the objective evaluation and comparison of research in biomedical ontology. The objective, quantifiable comparison of research results based on scientific applications opens up the possibility for systematically improving the utility of ontologies in biomedical research.

  5. EXTRACT

    DEFF Research Database (Denmark)

    Pafilis, Evangelos; Buttigieg, Pier Luigi; Ferrell, Barbra

    2016-01-01

    The microbial and molecular ecology research communities have made substantial progress on developing standards for annotating samples with environment metadata. However, sample manual annotation is a highly labor intensive process and requires familiarity with the terminologies used. We have the...... and text-mining-assisted curation revealed that EXTRACT speeds up annotation by 15-25% and helps curators to detect terms that would otherwise have been missed.Database URL: https://extract.hcmr.gr/....

  6. Automated Building Extraction from High-Resolution Satellite Imagery in Urban Areas Using Structural, Contextual, and Spectral Information

    Directory of Open Access Journals (Sweden)

    Curt H. Davis

    2005-08-01

    Full Text Available High-resolution satellite imagery provides an important new data source for building extraction. We demonstrate an integrated strategy for identifying buildings in 1-meter resolution satellite imagery of urban areas. Buildings are extracted using structural, contextual, and spectral information. First, a series of geodesic opening and closing operations are used to build a differential morphological profile (DMP that provides image structural information. Building hypotheses are generated and verified through shape analysis applied to the DMP. Second, shadows are extracted using the DMP to provide reliable contextual information to hypothesize position and size of adjacent buildings. Seed building rectangles are verified and grown on a finely segmented image. Next, bright buildings are extracted using spectral information. The extraction results from the different information sources are combined after independent extraction. Performance evaluation of the building extraction on an urban test site using IKONOS satellite imagery of the City of Columbia, Missouri, is reported. With the combination of structural, contextual, and spectral information, 72.7% of the building areas are extracted with a quality percentage 58.8%.

  7. A Feature Extraction Method Based on Information Theory for Fault Diagnosis of Reciprocating Machinery

    Science.gov (United States)

    Wang, Huaqing; Chen, Peng

    2009-01-01

    This paper proposes a feature extraction method based on information theory for fault diagnosis of reciprocating machinery. A method to obtain symptom parameter waves is defined in the time domain using the vibration signals, and an information wave is presented based on information theory, using the symptom parameter waves. A new way to determine the difference spectrum of envelope information waves is also derived, by which the feature spectrum can be extracted clearly and machine faults can be effectively differentiated. This paper also compares the proposed method with the conventional Hilbert-transform-based envelope detection and with a wavelet analysis technique. Practical examples of diagnosis for a rolling element bearing used in a diesel engine are provided to verify the effectiveness of the proposed method. The verification results show that the bearing faults that typically occur in rolling element bearings, such as outer-race, inner-race, and roller defects, can be effectively identified by the proposed method, while these bearing faults are difficult to detect using either of the other techniques it was compared to. PMID:22574021

  8. A Feature Extraction Method Based on Information Theory for Fault Diagnosis of Reciprocating Machinery

    Directory of Open Access Journals (Sweden)

    Huaqing Wang

    2009-04-01

    Full Text Available This paper proposes a feature extraction method based on information theory for fault diagnosis of reciprocating machinery. A method to obtain symptom parameter waves is defined in the time domain using the vibration signals, and an information wave is presented based on information theory, using the symptom parameter waves. A new way to determine the difference spectrum of envelope information waves is also derived, by which the feature spectrum can be extracted clearly and machine faults can be effectively differentiated. This paper also compares the proposed method with the conventional Hilbert-transform-based envelope detection and with a wavelet analysis technique. Practical examples of diagnosis for a rolling element bearing used in a diesel engine are provided to verify the effectiveness of the proposed method. The verification results show that the bearing faults that typically occur in rolling element bearings, such as outer-race, inner-race, and roller defects, can be effectively identified by the proposed method, while these bearing faults are difficult to detect using either of the other techniques it was compared to.

  9. A novel lossless robust watermarking method for copyright protection of biomedical image.

    Science.gov (United States)

    Chen, Zhigang; Deng, Xiaohong; Zeng, Feng; Liu, Huiwen; Chen, Liang

    2013-03-01

    Nanoscience and Nanotechnology promotes the development of biomedical imaging devices, more and more valuable biomedical images are transmitted through the open network, and their copyright suffers a major challenge. This paper proposes a new lossless robust watermarking method to realize biomedical image's copyright protection. For high-resolution biomedical images, the redundant theory and histogram shifting method based on image block's difference are utilized to repeatedly embed copyright watermark into different color channels. In the extracting procedure, each layer's watermark information can be extracted from watermarked image respectively, and the final watermark is judged by the voting theory. The redundant scheme and voting theory guarantees the watermark can resist against random noise's attack well. Besides, in order to reduce the watermark overhead in embedding procedure, the histogram narrowing down technique is used to tackle with those image blocks would overflows and underflows. Experimental results showed that the proposed method outperformed the existing semi-fragile reversible watermarking scheme and provided a great robustness against moderate JPEG compression and salt-pepper and Gaussian noise.

  10. The Feature Extraction Based on Texture Image Information for Emotion Sensing in Speech

    Directory of Open Access Journals (Sweden)

    Kun-Ching Wang

    2014-09-01

    Full Text Available In this paper, we present a novel texture image feature for Emotion Sensing in Speech (ESS. This idea is based on the fact that the texture images carry emotion-related information. The feature extraction is derived from time-frequency representation of spectrogram images. First, we transform the spectrogram as a recognizable image. Next, we use a cubic curve to enhance the image contrast. Then, the texture image information (TII derived from the spectrogram image can be extracted by using Laws’ masks to characterize emotional state. In order to evaluate the effectiveness of the proposed emotion recognition in different languages, we use two open emotional databases including the Berlin Emotional Speech Database (EMO-DB and eNTERFACE corpus and one self-recorded database (KHUSC-EmoDB, to evaluate the performance cross-corpora. The results of the proposed ESS system are presented using support vector machine (SVM as a classifier. Experimental results show that the proposed TII-based feature extraction inspired by visual perception can provide significant classification for ESS systems. The two-dimensional (2-D TII feature can provide the discrimination between different emotions in visual expressions except for the conveyance pitch and formant tracks. In addition, the de-noising in 2-D images can be more easily completed than de-noising in 1-D speech.

  11. An Accurate Integral Method for Vibration Signal Based on Feature Information Extraction

    Directory of Open Access Journals (Sweden)

    Yong Zhu

    2015-01-01

    Full Text Available After summarizing the advantages and disadvantages of current integral methods, a novel vibration signal integral method based on feature information extraction was proposed. This method took full advantage of the self-adaptive filter characteristic and waveform correction feature of ensemble empirical mode decomposition in dealing with nonlinear and nonstationary signals. This research merged the superiorities of kurtosis, mean square error, energy, and singular value decomposition on signal feature extraction. The values of the four indexes aforementioned were combined into a feature vector. Then, the connotative characteristic components in vibration signal were accurately extracted by Euclidean distance search, and the desired integral signals were precisely reconstructed. With this method, the interference problem of invalid signal such as trend item and noise which plague traditional methods is commendably solved. The great cumulative error from the traditional time-domain integral is effectively overcome. Moreover, the large low-frequency error from the traditional frequency-domain integral is successfully avoided. Comparing with the traditional integral methods, this method is outstanding at removing noise and retaining useful feature information and shows higher accuracy and superiority.

  12. National information service in mining, mineral processing and extractive metallurgy. [MINTEC

    Energy Technology Data Exchange (ETDEWEB)

    Romaniuk, A.S.; MacDonald, R.J.C.

    1979-03-01

    More than a dedade ago, CANMET management recognized the need to make better use of existing technological information in mining and extractive metallurgy, two fields basic to the economic well-being of Canada. There were at that time no indexes or files didicated to disseminating technical information for the many minerals mined and processed in Canada, including coal. CANMET, with the nation's largest research and library resources in the minerals field, was in a unique position to fill this need. Initial efforts were concentrated on building a mining file beginning with identification of world sources of published information, development of a special thesaurus of terms for language control and adoption of a manual indexing/retrieval system. By early 1973, this file held 8,300 references, with source, abstract and keywords given for each reference. In mid-1973, operations were computerized. Software for indexing and retrieval by batch mode was written by CANMET staff to utilize the hardware facilities of EMR's Computer Science Center. The resulting MINTEC file, one of the few files of technological information produced in Canada, is the basis for the national literature search service in mining offered by CANMET. Attention is now focussed on building a sister-file in extractive metallurgy using the system already developed. Published information sources have been identified and a thesaurus of terms is being compiled and tested. The software developed for CANMET's file-building operations has several features, including the selective dissemination of information and production from magnetic tape of photoready copy for publication, as in a bi-monthly abstracts journal.

  13. Taming Big Data: An Information Extraction Strategy for Large Clinical Text Corpora.

    Science.gov (United States)

    Gundlapalli, Adi V; Divita, Guy; Carter, Marjorie E; Redd, Andrew; Samore, Matthew H; Gupta, Kalpana; Trautner, Barbara

    2015-01-01

    Concepts of interest for clinical and research purposes are not uniformly distributed in clinical text available in electronic medical records. The purpose of our study was to identify filtering techniques to select 'high yield' documents for increased efficacy and throughput. Using two large corpora of clinical text, we demonstrate the identification of 'high yield' document sets in two unrelated domains: homelessness and indwelling urinary catheters. For homelessness, the high yield set includes homeless program and social work notes. For urinary catheters, concepts were more prevalent in notes from hospitalized patients; nursing notes accounted for a majority of the high yield set. This filtering will enable customization and refining of information extraction pipelines to facilitate extraction of relevant concepts for clinical decision support and other uses.

  14. Note: Sound recovery from video using SVD-based information extraction

    Science.gov (United States)

    Zhang, Dashan; Guo, Jie; Lei, Xiujun; Zhu, Chang'an

    2016-08-01

    This note reports an efficient singular value decomposition (SVD)-based vibration extraction approach that recovers sound information in silent high-speed video. A high-speed camera of which frame rates are in the range of 2 kHz-10 kHz is applied to film the vibrating objects. Sub-images cut from video frames are transformed into column vectors and then reconstructed to a new matrix. The SVD of the new matrix produces orthonormal image bases (OIBs) and image projections onto specific OIB can be recovered as understandable acoustical signals. Standard frequencies of 256 Hz and 512 Hz tuning forks are extracted offline from their vibrating surfaces and a 3.35 s speech signal is recovered online from a piece of paper that is stimulated by sound waves within 1 min.

  15. Review of Biomedical Image Processing

    Directory of Open Access Journals (Sweden)

    Ciaccio Edward J

    2011-11-01

    Full Text Available Abstract This article is a review of the book: 'Biomedical Image Processing', by Thomas M. Deserno, which is published by Springer-Verlag. Salient information that will be useful to decide whether the book is relevant to topics of interest to the reader, and whether it might be suitable as a course textbook, are presented in the review. This includes information about the book details, a summary, the suitability of the text in course and research work, the framework of the book, its specific content, and conclusions.

  16. Handbook of photonics for biomedical engineering

    CERN Document Server

    Kim, Donghyun; Somekh, Michael

    2017-01-01

    Nanophotonics has emerged rapidly into technological mainstream with the advent and maturity of nanotechnology available in photonics and enabled many new exciting applications in the area of biomedical science and engineering that were unimagined even a few years ago with conventional photonic engineering techniques. Handbook of Nanophotonics in Biomedical Engineering is intended to be a reliable resource to a wealth of information on nanophotonics that can inspire readers by detailing emerging and established possibilities of nanophotonics in biomedical science and engineering applications. This comprehensive reference presents not only the basics of nanophotonics but also explores recent experimental and clinical methods used in biomedical and bioengineering research. Each peer-reviewed chapter of this book discusses fundamental aspects and materials/fabrication issues of nanophotonics, as well as applications in interfaces, cell, tissue, animal studies, and clinical engineering. The organization provides ...

  17. Automated DICOM metadata and volumetric anatomical information extraction for radiation dosimetry

    Science.gov (United States)

    Papamichail, D.; Ploussi, A.; Kordolaimi, S.; Karavasilis, E.; Papadimitroulas, P.; Syrgiamiotis, V.; Efstathopoulos, E.

    2015-09-01

    Patient-specific dosimetry calculations based on simulation techniques have as a prerequisite the modeling of the modality system and the creation of voxelized phantoms. This procedure requires the knowledge of scanning parameters and patients’ information included in a DICOM file as well as image segmentation. However, the extraction of this information is complicated and time-consuming. The objective of this study was to develop a simple graphical user interface (GUI) to (i) automatically extract metadata from every slice image of a DICOM file in a single query and (ii) interactively specify the regions of interest (ROI) without explicit access to the radiology information system. The user-friendly application developed in Matlab environment. The user can select a series of DICOM files and manage their text and graphical data. The metadata are automatically formatted and presented to the user as a Microsoft Excel file. The volumetric maps are formed by interactively specifying the ROIs and by assigning a specific value in every ROI. The result is stored in DICOM format, for data and trend analysis. The developed GUI is easy, fast and and constitutes a very useful tool for individualized dosimetry. One of the future goals is to incorporate a remote access to a PACS server functionality.

  18. Information extraction approaches to unconventional data sources for "Injury Surveillance System": the case of newspapers clippings.

    Science.gov (United States)

    Berchialla, Paola; Scarinzi, Cecilia; Snidero, Silvia; Rahim, Yousif; Gregori, Dario

    2012-04-01

    Injury Surveillance Systems based on traditional hospital records or clinical data have the advantage of being a well established, highly reliable source of information for making an active surveillance on specific injuries, like choking in children. However, they suffer the drawback of delays in making data available to the analysis, due to inefficiencies in data collection procedures. In this sense, the integration of clinical based registries with unconventional data sources like newspaper articles has the advantage of making the system more useful for early alerting. Usage of such sources is difficult since information is only available in the form of free natural-language documents rather than structured databases as required by traditional data mining techniques. Information Extraction (IE) addresses the problem of transforming a corpus of textual documents into a more structured database. In this paper, on a corpora of Italian newspapers articles related to choking in children due to ingestion/inhalation of foreign body we compared the performance of three IE algorithms- (a) a classical rule based system which requires a manual annotation of the rules; (ii) a rule based system which allows for the automatic building of rules; (b) a machine learning method based on Support Vector Machine. Although some useful indications are extracted from the newspaper clippings, this approach is at the time far from being routinely implemented for injury surveillance purposes.

  19. Powering biomedical devices

    CERN Document Server

    Romero, Edwar

    2013-01-01

    From exoskeletons to neural implants, biomedical devices are no less than life-changing. Compact and constant power sources are necessary to keep these devices running efficiently. Edwar Romero's Powering Biomedical Devices reviews the background, current technologies, and possible future developments of these power sources, examining not only the types of biomedical power sources available (macro, mini, MEMS, and nano), but also what they power (such as prostheses, insulin pumps, and muscular and neural stimulators), and how they work (covering batteries, biofluids, kinetic and ther

  20. Biomedical applications of polymers

    CERN Document Server

    Gebelein, C G

    1991-01-01

    The biomedical applications of polymers span an extremely wide spectrum of uses, including artificial organs, skin and soft tissue replacements, orthopaedic applications, dental applications, and controlled release of medications. No single, short review can possibly cover all these items in detail, and dozens of books andhundreds of reviews exist on biomedical polymers. Only a few relatively recent examples will be cited here;additional reviews are listed under most of the major topics in this book. We will consider each of the majorclassifications of biomedical polymers to some extent, inclu

  1. Biomedical engineering fundamentals

    CERN Document Server

    Bronzino, Joseph D; Bronzino, Joseph D

    2006-01-01

    Over the last century,medicine has come out of the "black bag" and emerged as one of the most dynamic and advanced fields of development in science and technology. Today, biomedical engineering plays a critical role in patient diagnosis, care, and rehabilitation. As such, the field encompasses a wide range of disciplines, from biology and physiology to informatics and signal processing. Reflecting the enormous growth and change in biomedical engineering during the infancy of the 21st century, The Biomedical Engineering Handbook enters its third edition as a set of three carefully focused and

  2. Biomedical Engineering Desk Reference

    CERN Document Server

    Ratner, Buddy D; Schoen, Frederick J; Lemons, Jack E; Dyro, Joseph; Martinsen, Orjan G; Kyle, Richard; Preim, Bernhard; Bartz, Dirk; Grimnes, Sverre; Vallero, Daniel; Semmlow, John; Murray, W Bosseau; Perez, Reinaldo; Bankman, Isaac; Dunn, Stanley; Ikada, Yoshito; Moghe, Prabhas V; Constantinides, Alkis

    2009-01-01

    A one-stop Desk Reference, for Biomedical Engineers involved in the ever expanding and very fast moving area; this is a book that will not gather dust on the shelf. It brings together the essential professional reference content from leading international contributors in the biomedical engineering field. Material covers a broad range of topics including: Biomechanics and Biomaterials; Tissue Engineering; and Biosignal Processing* A hard-working desk reference providing all the essential material needed by biomedical and clinical engineers on a day-to-day basis * Fundamentals, key techniques,

  3. Handbook of biomedical optics

    CERN Document Server

    Boas, David A

    2011-01-01

    Biomedical optics holds tremendous promise to deliver effective, safe, non- or minimally invasive diagnostics and targeted, customizable therapeutics. Handbook of Biomedical Optics provides an in-depth treatment of the field, including coverage of applications for biomedical research, diagnosis, and therapy. It introduces the theory and fundamentals of each subject, ensuring accessibility to a wide multidisciplinary readership. It also offers a view of the state of the art and discusses advantages and disadvantages of various techniques.Organized into six sections, this handbook: Contains intr

  4. Using Local Grammar for Entity Extraction from Clinical Reports

    Directory of Open Access Journals (Sweden)

    Aicha Ghoulam

    2015-06-01

    Full Text Available Information Extraction (IE is a natural language processing (NLP task whose aim is to analyze texts written in natural language to extract structured and useful information such as named entities and semantic relations linking these entities. Information extraction is an important task for many applications such as bio-medical literature mining, customer care, community websites, and personal information management. The increasing information available in patient clinical reports is difficult to access. As it is often in an unstructured text form, doctors need tools to enable them access to this information and the ability to search it. Hence, a system for extracting this information in a structured form can benefits healthcare professionals. The work presented in this paper uses a local grammar approach to extract medical named entities from French patient clinical reports. Experimental results show that the proposed approach achieved an F-Measure of 90. 06%.

  5. Analysis on health information extracted from an urban professional population in Beijing

    Institute of Scientific and Technical Information of China (English)

    ZHANG Tie-mei; ZHANG Yan; LIU Bin; JIA Hong-bo; LIU Yun-jie; ZHU Ling; LUO Sen-lin; HAN Yi-wen; ZHANG Yan; YANG Shu-wen; LIU An-nan; MA Lan-jun; ZHAO Yan-yan

    2011-01-01

    Background The assembled data from a population could provide information on health trends within the population.The aim of this research was to extract and know basic health information from an urban professional population in Beijing.Methods Data analysis was carried out in a population who underwent a routine medical check-up and aged >20 years,including 30 058 individuals.General information,data from physical examinations and blood samples were collected in the same method.The health status was separated into three groups by the criteria generated in this study,i.e.,people with common chronic diseases,people in a sub-clinic situation,and healthy people.The proportion of both common diseases suffered and health risk distribution of different age groups were also analyzed.Results The proportion of people with common chronic diseases,in the sub-clinic group and in the healthy group was 28.6%,67.8% and 3.6% respectively.There were significant differences in the health situation in different age groups.Hypertension was on the top of list of self-reported diseases.The proportion of chronic diseases increased significantly in people after 35 years of age.Meanwhile,the proportion of sub-clinic conditions was decreasing at the same rate.The complex risk factors to health in this population were metabolic disturbances (61.3%),risk for tumor (2.7%),abnormal results of morphological examination (8.2%) and abnormal results of lab tests of serum (27.8%).Conclusions Health information could be extracted from a complex data set from the heath check-ups of the general population.The information should be applied to support prevention and control chronic diseases as well as for directing intervention for patients with risk factors for disease.

  6. Red Tide Information Extraction Based on Multi-source Remote Sensing Data in Haizhou Bay

    Institute of Scientific and Technical Information of China (English)

    2011-01-01

    [Objective] The aim was to extract red tide information in Haizhou Bay on the basis of multi-source remote sensing data.[Method] Red tide in Haizhou Bay was studied based on multi-source remote sensing data,such as IRS-P6 data on October 8,2005,Landsat 5-TM data on May 20,2006,MODIS 1B data on October 6,2006 and HY-1B second-grade data on April 22,2009,which were firstly preprocessed through geometric correction,atmospheric correction,image resizing and so on.At the same time,the synchronous environment mon...

  7. Multi-Paradigm and Multi-Lingual Information Extraction as Support for Medical Web Labelling Authorities

    Directory of Open Access Journals (Sweden)

    Martin Labsky

    2010-10-01

    Full Text Available Until recently, quality labelling of medical web content has been a pre-dominantly manual activity. However, the advances in automated text processing opened the way to computerised support of this activity. The core enabling technology is information extraction (IE. However, the heterogeneity of websites offering medical content imposes particular requirements on the IE techniques to be applied. In the paper we discuss these requirements and describe a multi-paradigm approach to IE addressing them. Experiments on multi-lingual data are reported. The research has been carried out within the EU MedIEQ project.

  8. The method of earthquake landslide information extraction with high-resolution remote sensing

    Science.gov (United States)

    Wu, Jian; Chen, Peng; Liu, Yaolin; Wang, Jing

    2014-05-01

    As a kind of secondary geological disaster caused by strong earthquake, the earthquake-induced landslide has drawn much attention in the world due to the severe hazard. The high-resolution remote sensing, as a new technology for investigation and monitoring, has been widely applied in landslide susceptibility and hazard mapping. The Ms 8.0 Wenchuan earthquake, occurred on 12 May 2008, caused many buildings collapse and half million people be injured. Meanwhile, damage caused by earthquake-induced landslides, collapse and debris flow became the major part of total losses. By analyzing the property of the Zipingpu landslide occurred in the Wenchuan earthquake, the present study advanced a quick-and-effective way for landslide extraction based on NDVI and slope information, and the results were validated with pixel-oriented and object-oriented methods. The main advantage of the idea lies in the fact that it doesn't need much professional knowledge and data such as crustal movement, geological structure, fractured zone, etc. and the researchers can provide the landslide monitoring information for earthquake relief as soon as possible. In pixel-oriented way, the NDVI-differential image as well as slope image was analyzed and segmented to extract the landslide information. When it comes to object-oriented method, the multi-scale segmentation algorithm was applied in order to build up three-layer hierarchy. The spectral, textural, shape, location and contextual information of individual object classes, and GLCM (Grey Level Concurrence Matrix homogeneity, shape index etc. were extracted and used to establish the fuzzy decision rule system of each layer for earthquake landslide extraction. Comparison of the results generated from the two methods, showed that the object-oriented method could successfully avoid the phenomenon of NDVI-differential bright noise caused by the spectral diversity of high-resolution remote sensing data and achieved better result with an overall

  9. Construction of information service platform for biomedical industry groups%构建面向生物医药产业集群的信息服务平台

    Institute of Scientific and Technical Information of China (English)

    赵颖颖; 张晗; 赵玉虹

    2016-01-01

    The construction plan of information service platform for biomedical industry groups was proposed, including expert intelligence database, special database, advanced information service platform and biomedical achievements transformation platform.The information ( including names, subject fields and research interests of experts) in expert intelligence database can be searched according to the subject fields and research interests of experts.The special database is consisted of database of special literature, genes, proteins, special drugs, achievements, patents and demands.The information service platform can provide literature retrieval service, literature novelty assessment service, data-mining service, information analysis service, decision-making support service, and competitive informa-tion service.The biomedical achievements transformation platform can provide service for transforming achievements and for solving difficulty demand problems.%提出了搭建面向生物医药产业集群的信息服务平台的建设方案,包括专家智库、专题数据库、高端信息服务平台和生物医药成果转化平台.其中,专家智库包含的专家姓名、学科领域、研究方向等专家信息,可通过学科领域和研究方向进行检索,专题数据库包括专题文献库、基因专题库、蛋白专题库、专题药品库、成果库、专利库和需求库等;信息服务平台提供文献检索、科技查新、数据挖掘、信息分析、决策支持、竞争情报等信息服务,成果转化平台可提供转化成果专利和解决需求难题服务.

  10. Sensors for biomedical applications

    NARCIS (Netherlands)

    Bergveld, Piet

    1986-01-01

    This paper considers the impact during the last decade of modern IC technology, microelectronics, thin- and thick-film technology, fibre optic technology, etc. on the development of sensors for biomedical applications.

  11. The information extraction of Gannan citrus orchard based on the GF-1 remote sensing image

    Science.gov (United States)

    Wang, S.; Chen, Y. L.

    2017-02-01

    The production of Gannan oranges is the largest in China, which occupied an important part in the world. The extraction of citrus orchard quickly and effectively has important significance for fruit pathogen defense, fruit production and industrial planning. The traditional spectra extraction method of citrus orchard based on pixel has a lower classification accuracy, difficult to avoid the “pepper phenomenon”. In the influence of noise, the phenomenon that different spectrums of objects have the same spectrum is graveness. Taking Xunwu County citrus fruit planting area of Ganzhou as the research object, aiming at the disadvantage of the lower accuracy of the traditional method based on image element classification method, a decision tree classification method based on object-oriented rule set is proposed. Firstly, multi-scale segmentation is performed on the GF-1 remote sensing image data of the study area. Subsequently the sample objects are selected for statistical analysis of spectral features and geometric features. Finally, combined with the concept of decision tree classification, a variety of empirical values of single band threshold, NDVI, band combination and object geometry characteristics are used hierarchically to execute the information extraction of the research area, and multi-scale segmentation and hierarchical decision tree classification is implemented. The classification results are verified with the confusion matrix, and the overall Kappa index is 87.91%.

  12. Statistics in biomedical research

    OpenAIRE

    González-Manteiga, Wenceslao; Cadarso-Suárez, Carmen

    2007-01-01

    The discipline of biostatistics is nowadays a fundamental scientific component of biomedical, public health and health services research. Traditional and emerging areas of application include clinical trials research, observational studies, physiology, imaging, and genomics. The present article reviews the current situation of biostatistics, considering the statistical methods traditionally used in biomedical research, as well as the ongoing development of new methods in response to the new p...

  13. Biomedical signal processing

    CERN Document Server

    Akay, Metin

    1994-01-01

    Sophisticated techniques for signal processing are now available to the biomedical specialist! Written in an easy-to-read, straightforward style, Biomedical Signal Processing presents techniques to eliminate background noise, enhance signal detection, and analyze computer data, making results easy to comprehend and apply. In addition to examining techniques for electrical signal analysis, filtering, and transforms, the author supplies an extensive appendix with several computer programs that demonstrate techniques presented in the text.

  14. Biomedical signal analysis

    CERN Document Server

    Rangayyan, Rangaraj M

    2015-01-01

    The book will help assist a reader in the development of techniques for analysis of biomedical signals and computer aided diagnoses with a pedagogical examination of basic and advanced topics accompanied by over 350 figures and illustrations. Wide range of filtering techniques presented to address various applications. 800 mathematical expressions and equations. Practical questions, problems and laboratory exercises. Includes fractals and chaos theory with biomedical applications.

  15. Detailed design specification for the ALT Shuttle Information Extraction Subsystem (SIES)

    Science.gov (United States)

    Clouette, G. L.; Fitzpatrick, W. N.

    1976-01-01

    The approach and landing test (ALT) shuttle information extraction system (SIES) is described in terms of general requirements and system characteristics output products and processing options, output products and data sources, and system data flow. The ALT SIES is a data reduction system designed to satisfy certain data processing requirements for the ALT phase of the space shuttle program. The specific ALT SIES data processing requirements are stated in the data reduction complex approach and landing test data processing requirements. In general, ALT SIES must produce time correlated data products as a result of standardized data reduction or special purpose analytical processes. The main characteristics of ALT SIES are: (1) the system operates in a batch (non-interactive) mode; (2) the processing is table driven; (3) it is data base oriented; (4) it has simple operating procedures; and (5) it requires a minimum of run time information.

  16. Solution of Multiple——Point Statistics to Extracting Information from Remotely Sensed Imagery

    Institute of Scientific and Technical Information of China (English)

    Ge Yong; Bai Hexiang; Cheng Qiuming

    2008-01-01

    Two phenomena of similar objects with different spectra and different objects with similar spectrum often result in the difficulty of separation and identification of all types of geographical objects only using spectral information.Therefore,there is a need to incorporate spatial structural and spatial association properties of the surfaces of objects into image processing to improve the accuracy of classification of remotely sensed imagery.In the current article,a new method is proposed on the basis of the principle of multiple-point statistics for combining spectral information and spatial information for image classification.The method was validated by applying to a case study on road extraction based on Landsat TM taken over the Chinese YeHow River delta on August 8,1999. The classification results have shown that this new method provides overall better results than the traditional methods such as maximum likelihood classifier (MLC)

  17. Foreground and Background Lexicons and Word Sense Disambiguation for Information Extraction

    CERN Document Server

    Kilgarriff, A

    1999-01-01

    Lexicon acquisition from machine-readable dictionaries and corpora is currently a dynamic field of research, yet it is often not clear how lexical information so acquired can be used, or how it relates to structured meaning representations. In this paper I look at this issue in relation to Information Extraction (hereafter IE), and one subtask for which both lexical and general knowledge are required, Word Sense Disambiguation (WSD). The analysis is based on the widely-used, but little-discussed distinction between an IE system's foreground lexicon, containing the domain's key terms which map onto the database fields of the output formalism, and the background lexicon, containing the remainder of the vocabulary. For the foreground lexicon, human lexicography is required. For the background lexicon, automatic acquisition is appropriate. For the foreground lexicon, WSD will occur as a by-product of finding a coherent semantic interpretation of the input. WSD techniques as discussed in recent literature are suit...

  18. Audio-Visual Speech Recognition Using Lip Information Extracted from Side-Face Images

    Directory of Open Access Journals (Sweden)

    Koji Iwano

    2007-03-01

    Full Text Available This paper proposes an audio-visual speech recognition method using lip information extracted from side-face images as an attempt to increase noise robustness in mobile environments. Our proposed method assumes that lip images can be captured using a small camera installed in a handset. Two different kinds of lip features, lip-contour geometric features and lip-motion velocity features, are used individually or jointly, in combination with audio features. Phoneme HMMs modeling the audio and visual features are built based on the multistream HMM technique. Experiments conducted using Japanese connected digit speech contaminated with white noise in various SNR conditions show effectiveness of the proposed method. Recognition accuracy is improved by using the visual information in all SNR conditions. These visual features were confirmed to be effective even when the audio HMM was adapted to noise by the MLLR method.

  19. Audio-Visual Speech Recognition Using Lip Information Extracted from Side-Face Images

    Directory of Open Access Journals (Sweden)

    Iwano Koji

    2007-01-01

    Full Text Available This paper proposes an audio-visual speech recognition method using lip information extracted from side-face images as an attempt to increase noise robustness in mobile environments. Our proposed method assumes that lip images can be captured using a small camera installed in a handset. Two different kinds of lip features, lip-contour geometric features and lip-motion velocity features, are used individually or jointly, in combination with audio features. Phoneme HMMs modeling the audio and visual features are built based on the multistream HMM technique. Experiments conducted using Japanese connected digit speech contaminated with white noise in various SNR conditions show effectiveness of the proposed method. Recognition accuracy is improved by using the visual information in all SNR conditions. These visual features were confirmed to be effective even when the audio HMM was adapted to noise by the MLLR method.

  20. Marine Collagen: An Emerging Player in Biomedical applications.

    Science.gov (United States)

    Subhan, Fazli; Ikram, Muhammad; Shehzad, Adeeb; Ghafoor, Abdul

    2015-08-01

    Mammalian collagen is a multifactorial biomaterial that is widely used for beneficial purposes in the advanced biomedical technologies. Generally, biomedical applicable collagen is extracted from the mammalian body, but it can also be derived from marine species. Recently, mammalian tissues collagen proteins are considered a great pathological risk for transmitted diseases, because purification of such protein is very challenging and needs efficient tool to avoid structure alteration. Thus, difficult extraction process and high cost decreased mammalian collagen demands for beneficial effects compared to marine collagen. In contrast, marine collagen is safe and easy to extract, however this potential source of collagen is hindered by low denaturing temperature, which is considered a main hurdle in the beneficial effects of marine collagen. Characterization and biomedical applications of marine collagen are in transition state and yet to be discovered. Therefore, an attempt was made to summarize the recent knowledge regarding different aspects of marine collagen applications in the biomedical engineering field.

  1. An Investigation of the Relationship Between Automated Machine Translation Evaluation Metrics and User Performance on an Information Extraction Task

    Science.gov (United States)

    2007-01-01

    AN INFORMATION EXTRACTION TASK Calandra Rilette Tate, Doctor of Philosophy, 2007 Dissertation directed by: Professor Eric V. Slud Department of...User Performance on an Information Extraction Task by Calandra Rilette Tate Dissertation submitted to the Faculty of the Graduate School of the...Calandra Rilette Tate 2007 DEDICATION This work is dedicated to two of my greatest influencers—there since the be- ginning, but unfortunately unable to

  2. [An object-based information extraction technology for dominant tree species group types].

    Science.gov (United States)

    Tian, Tian; Fan, Wen-yi; Lu, Wei; Xiao, Xiang

    2015-06-01

    Information extraction for dominant tree group types is difficult in remote sensing image classification, howevers, the object-oriented classification method using high spatial resolution remote sensing data is a new method to realize the accurate type information extraction. In this paper, taking the Jiangle Forest Farm in Fujian Province as the research area, based on the Quickbird image data in 2013, the object-oriented method was adopted to identify the farmland, shrub-herbaceous plant, young afforested land, Pinus massoniana, Cunninghamia lanceolata and broad-leave tree types. Three types of classification factors including spectral, texture, and different vegetation indices were used to establish a class hierarchy. According to the different levels, membership functions and the decision tree classification rules were adopted. The results showed that the method based on the object-oriented method by using texture, spectrum and the vegetation indices achieved the classification accuracy of 91.3%, which was increased by 5.7% compared with that by only using the texture and spectrum.

  3. Extracting Urban Ground Object Information from Images and LiDAR Data

    Science.gov (United States)

    Yi, Lina; Zhao, Xuesheng; Li, Luan; Zhang, Guifeng

    2016-06-01

    To deal with the problem of urban ground object information extraction, the paper proposes an object-oriented classification method using aerial image and LiDAR data. Firstly, we select the optimal segmentation scales of different ground objects and synthesize them to get accurate object boundaries. Then, this paper uses ReliefF algorithm to select the optimal feature combination and eliminate the Hughes phenomenon. Eventually, the multiple classifier combination method is applied to get the outcome of the classification. In order to validate the feasible of this method, this paper selects two experimental regions in Stuttgart and Germany (Region A and B, covers 0.21 km2 and 1.1 km2 respectively). The aim of the first experiment on the Region A is to get the optimal segmentation scales and classification features. The overall accuracy of the classification reaches to 93.3 %. The purpose of the experiment on region B is to validate the application-ability of this method for a large area, which is turned out to be reaches 88.4 % overall accuracy. In the end of this paper, the conclusion shows that the proposed method can be performed accurately and efficiently in terms of urban ground information extraction and be of high application value.

  4. High-resolution multispectral satellite imagery for extracting bathymetric information of Antarctic shallow lakes

    Science.gov (United States)

    Jawak, Shridhar D.; Luis, Alvarinho J.

    2016-05-01

    High-resolution pansharpened images from WorldView-2 were used for bathymetric mapping around Larsemann Hills and Schirmacher oasis, east Antarctica. We digitized the lake features in which all the lakes from both the study areas were manually extracted. In order to extract the bathymetry values from multispectral imagery we used two different models: (a) Stumpf model and (b) Lyzenga model. Multiband image combinations were used to improve the results of bathymetric information extraction. The derived depths were validated against the in-situ measurements and root mean square error (RMSE) was computed. We also quantified the error between in-situ and satellite-estimated lake depth values. Our results indicated a high correlation (R = 0.60 0.80) between estimated depth and in-situ depth measurements, with RMSE ranging from 0.10 to 1.30 m. This study suggests that the coastal blue band in the WV-2 imagery could retrieve accurate bathymetry information compared to other bands. To test the effect of size and dimension of lake on bathymetry retrieval, we distributed all the lakes on the basis of size and depth (reference data), as some of the lakes were open, some were semi frozen and others were completely frozen. Several tests were performed on open lakes on the basis of size and depth. Based on depth, very shallow lakes provided better correlation (≈ 0.89) compared to shallow (≈ 0.67) and deep lakes (≈ 0.48). Based on size, large lakes yielded better correlation in comparison to medium and small lakes.

  5. 生物医学研究伦理审查信息系统的应用%Application of biomedical research ethics review information system

    Institute of Scientific and Technical Information of China (English)

    彭智才; 尚政琴

    2016-01-01

    目的:探讨生物医学研究伦理审查信息系统在医院生物医学研究伦理审查中的应用.方法:系统设计依据国际协调会议(ICH)、临床试验管理规范(GCP)、世界卫生组织与热带病研究部门(WHO/TDR)的《生物医学研究审查伦理委员会操作指南》以及世界卫生组织、发展伦理委员会审查能力的战略行动(WHO SIDCER)认证有关伦理委员会操作规范进行开发.结果:新型生物医学研究伦理审查系统的应用,解决了伦理委员会务实高效地开展伦理审查和研究者有效遵循伦理原则来开展研究的问题,实现了伦理审查的申请、受理、审查、传达决定以及跟踪审查等操作规程的电子程序化.结论:生物医学研究伦理审查系统的应用,使伦理审查流程更加合理,操作更加简捷,可极大提高医院伦理审查的工作效率,方便和规范伦理审查的文档管理,提升伦理审查的质量管理,对生物医学研究伦理审查工作具有重要意义.%Objective:To discuss the application of "ethical review of biomedical research" system in the hospital ethical review of biomedical research.Methods: To design based on the ICH GCP specification, WHO/TDR" biomedical research ethics committee guidelines" Systematic, WHO SIDCER authentication on the ethics committee specification development.Results: The application of this system can realize the ethical review application, acceptance, examination and decision, convey the follow-up review procedures for electronic program.Conclusion: "The ethical review of biomedical research ethics review" system to make process more reasonable, operation more convenient, greatly improves the work efficiency of the hospital ethics review, document management, facilitate and regulate the ethical review, enhance the quality of management ethics review, plays an important role inbiomedical research ethics review.

  6. Unsupervised biomedical named entity recognition: experiments with clinical and biological texts.

    Science.gov (United States)

    Zhang, Shaodian; Elhadad, Noémie

    2013-12-01

    Named entity recognition is a crucial component of biomedical natural language processing, enabling information extraction and ultimately reasoning over and knowledge discovery from text. Much progress has been made in the design of rule-based and supervised tools, but they are often genre and task dependent. As such, adapting them to different genres of text or identifying new types of entities requires major effort in re-annotation or rule development. In this paper, we propose an unsupervised approach to extracting named entities from biomedical text. We describe a stepwise solution to tackle the challenges of entity boundary detection and entity type classification without relying on any handcrafted rules, heuristics, or annotated data. A noun phrase chunker followed by a filter based on inverse document frequency extracts candidate entities from free text. Classification of candidate entities into categories of interest is carried out by leveraging principles from distributional semantics. Experiments show that our system, especially the entity classification step, yields competitive results on two popular biomedical datasets of clinical notes and biological literature, and outperforms a baseline dictionary match approach. Detailed error analysis provides a road map for future work.

  7. Extracting duration information in a picture category decoding task using hidden Markov Models

    Science.gov (United States)

    Pfeiffer, Tim; Heinze, Nicolai; Frysch, Robert; Deouell, Leon Y.; Schoenfeld, Mircea A.; Knight, Robert T.; Rose, Georg

    2016-04-01

    Objective. Adapting classifiers for the purpose of brain signal decoding is a major challenge in brain-computer-interface (BCI) research. In a previous study we showed in principle that hidden Markov models (HMM) are a suitable alternative to the well-studied static classifiers. However, since we investigated a rather straightforward task, advantages from modeling of the signal could not be assessed. Approach. Here, we investigate a more complex data set in order to find out to what extent HMMs, as a dynamic classifier, can provide useful additional information. We show for a visual decoding problem that besides category information, HMMs can simultaneously decode picture duration without an additional training required. This decoding is based on a strong correlation that we found between picture duration and the behavior of the Viterbi paths. Main results. Decoding accuracies of up to 80% could be obtained for category and duration decoding with a single classifier trained on category information only. Significance. The extraction of multiple types of information using a single classifier enables the processing of more complex problems, while preserving good training results even on small databases. Therefore, it provides a convenient framework for online real-life BCI utilizations.

  8. The Study on Height Information Extraction of Cultural Features in Remote Sensing Images Based on Shadow Areas

    Science.gov (United States)

    Bao-Ming, Z.; Hai-Tao, G.; Jun, L.; Zhi-Qing, L.; Hong, H.

    2011-09-01

    Cultural feature is important element in geospatial information library and the height information is important information of cultural features. The existences of the height information and its precision have direct influence over topographic map, especially the quality of large-scale and medium-scale topographic map, and the level of surveying and mapping support. There are a lot of methods about height information extraction, in which the main methods are ground survey (field direct measurement) spatial sensor and photogrammetric ways. However, automatic extraction is very tough. This paper has had an emphasis on segmentation algorithm on shadow areas under multiple constraints and realized automatic extraction of height information by using shadow. Binarization image can be obtained using gray threshold estimated under the multiple constraints. On the interesting area, spot elimination and region splitting are made. After region labeling and non-shadowed regions elimination, shadow area of cultural features can be found. Then height of the cultural features can be calculated using shadow length, sun altitude angle, azimuth angle, and sensor altitude angle, azimuth angle. A great many of experiments have shown that mean square error of the height information of cultural features extraction is close to 2 meter and automatic extraction rate is close to 70%.

  9. THE STUDY ON HEIGHT INFORMATION EXTRACTION OF CULTURAL FEATURES IN REMOTE SENSING IMAGES BASED ON SHADOW AREAS

    Directory of Open Access Journals (Sweden)

    Z. Bao-Ming

    2012-09-01

    Full Text Available Cultural feature is important element in geospatial information library and the height information is important information of cultural features. The existences of the height information and its precision have direct influence over topographic map, especially the quality of large-scale and medium-scale topographic map, and the level of surveying and mapping support. There are a lot of methods about height information extraction, in which the main methods are ground survey (field direct measurement spatial sensor and photogrammetric ways. However, automatic extraction is very tough. This paper has had an emphasis on segmentation algorithm on shadow areas under multiple constraints and realized automatic extraction of height information by using shadow. Binarization image can be obtained using gray threshold estimated under the multiple constraints. On the interesting area, spot elimination and region splitting are made. After region labeling and non-shadowed regions elimination, shadow area of cultural features can be found. Then height of the cultural features can be calculated using shadow length, sun altitude angle, azimuth angle, and sensor altitude angle, azimuth angle. A great many of experiments have shown that mean square error of the height information of cultural features extraction is close to 2 meter and automatic extraction rate is close to 70%.

  10. Transforming a research-oriented dataset for evaluation of tactical information extraction technologies

    Science.gov (United States)

    Roy, Heather; Kase, Sue E.; Knight, Joanne

    2016-05-01

    The most representative and accurate data for testing and evaluating information extraction technologies is real-world data. Real-world operational data can provide important insights into human and sensor characteristics, interactions, and behavior. However, several challenges limit the feasibility of experimentation with real-world operational data. Realworld data lacks the precise knowledge of a "ground truth," a critical factor for benchmarking progress of developing automated information processing technologies. Additionally, the use of real-world data is often limited by classification restrictions due to the methods of collection, procedures for processing, and tactical sensitivities related to the sources, events, or objects of interest. These challenges, along with an increase in the development of automated information extraction technologies, are fueling an emerging demand for operationally-realistic datasets for benchmarking. An approach to meet this demand is to create synthetic datasets, which are operationally-realistic yet unclassified in content. The unclassified nature of these unclassified synthetic datasets facilitates the sharing of data between military and academic researchers thus increasing coordinated testing efforts. This paper describes the expansion and augmentation of two synthetic text datasets, one initially developed through academic research collaborations with the Army. Both datasets feature simulated tactical intelligence reports regarding fictitious terrorist activity occurring within a counterinsurgency (COIN) operation. The datasets were expanded and augmented to create two military relevant datasets. The first resulting dataset was created by augmenting and merging the two to create a single larger dataset containing ground-truth. The second resulting dataset was restructured to more realistically represent the format and content of intelligence reports. The dataset transformation effort, the final datasets, and their

  11. Classification and Extraction of Urban Land-Use Information from High-Resolution Image Based on Object Multi-features

    Institute of Scientific and Technical Information of China (English)

    Kong Chunfang; Xu Kai; Wu Chonglong

    2006-01-01

    Urban land provides a suitable location for various economic activities which affect the development of surrounding areas. With rapid industrialization and urbanization, the contradictions in land-use become more noticeable. Urban administrators and decision-makers seek modern methods and technology to provide information support for urban growth. Recently, with the fast development of high-resolution sensor technology, more relevant data can be obtained, which is an advantage in studying the sustainable development of urban land-use. However, these data are only information sources and are a mixture of "information" and "noise". Processing, analysis and information extraction from remote sensing data is necessary to provide useful information. This paper extracts urban land-use information from a high-resolution image by using the multi-feature information of the image objects, and adopts an object-oriented image analysis approach and multi-scale image segmentation technology. A classification and extraction model is set up based on the multi-features of the image objects, in order to contribute to information for reasonable planning and effective management. This new image analysis approach offers a satisfactory solution for extracting information quickly and efficiently.

  12. Effective use of Latent Semantic Indexing and Computational Linguistics in Biological and Biomedical Applications

    Directory of Open Access Journals (Sweden)

    Hongyu eChen

    2013-01-01

    Full Text Available Text mining is rapidly becoming an essential technique for the annotation and analysis of large biological data sets. Biomedical literature currently increases at a rate of several thousand papers per week, making automated information retrieval methods the only feasible method of managing this expanding corpus. With the increasing prevalence of open-access journals and constant growth of publicly-available repositories of biomedical literature, literature mining has become much more effective with respect to the extraction of biomedically-relevant data. In recent years, text mining of popular databases such as MEDLINE has evolved from basic term-searches to more sophisticated natural language processing techniques, indexing and retrieval methods, structural analysis and integration of literature with associated metadata. In this review, we will focus on Latent Semantic Indexing (LSI, a computational linguistics technique increasingly used for a variety of biological purposes. It is noted for its ability to consistently outperform benchmark Boolean text searches and co-occurrence models at information retrieval and its power to extract indirect relationships within a data set. LSI has been used successfully to formulate new hypotheses, generate novel connections from existing data, and validate empirical data.

  13. Effective use of latent semantic indexing and computational linguistics in biological and biomedical applications.

    Science.gov (United States)

    Chen, Hongyu; Martin, Bronwen; Daimon, Caitlin M; Maudsley, Stuart

    2013-01-01

    Text mining is rapidly becoming an essential technique for the annotation and analysis of large biological data sets. Biomedical literature currently increases at a rate of several thousand papers per week, making automated information retrieval methods the only feasible method of managing this expanding corpus. With the increasing prevalence of open-access journals and constant growth of publicly-available repositories of biomedical literature, literature mining has become much more effective with respect to the extraction of biomedically-relevant data. In recent years, text mining of popular databases such as MEDLINE has evolved from basic term-searches to more sophisticated natural language processing techniques, indexing and retrieval methods, structural analysis and integration of literature with associated metadata. In this review, we will focus on Latent Semantic Indexing (LSI), a computational linguistics technique increasingly used for a variety of biological purposes. It is noted for its ability to consistently outperform benchmark Boolean text searches and co-occurrence models at information retrieval and its power to extract indirect relationships within a data set. LSI has been used successfully to formulate new hypotheses, generate novel connections from existing data, and validate empirical data.

  14. Integrating systems biology models and biomedical ontologies

    Directory of Open Access Journals (Sweden)

    de Bono Bernard

    2011-08-01

    Full Text Available Abstract Background Systems biology is an approach to biology that emphasizes the structure and dynamic behavior of biological systems and the interactions that occur within them. To succeed, systems biology crucially depends on the accessibility and integration of data across domains and levels of granularity. Biomedical ontologies were developed to facilitate such an integration of data and are often used to annotate biosimulation models in systems biology. Results We provide a framework to integrate representations of in silico systems biology with those of in vivo biology as described by biomedical ontologies and demonstrate this framework using the Systems Biology Markup Language. We developed the SBML Harvester software that automatically converts annotated SBML models into OWL and we apply our software to those biosimulation models that are contained in the BioModels Database. We utilize the resulting knowledge base for complex biological queries that can bridge levels of granularity, verify models based on the biological phenomenon they represent and provide a means to establish a basic qualitative layer on which to express the semantics of biosimulation models. Conclusions We establish an information flow between biomedical ontologies and biosimulation models and we demonstrate that the integration of annotated biosimulation models and biomedical ontologies enables the verification of models as well as expressive queries. Establishing a bi-directional information flow between systems biology and biomedical ontologies has the potential to enable large-scale analyses of biological systems that span levels of granularity from molecules to organisms.

  15. Enriching a document collection by integrating information extraction and PDF annotation

    Science.gov (United States)

    Powley, Brett; Dale, Robert; Anisimoff, Ilya

    2009-01-01

    Modern digital libraries offer all the hyperlinking possibilities of the World Wide Web: when a reader finds a citation of interest, in many cases she can now click on a link to be taken to the cited work. This paper presents work aimed at providing the same ease of navigation for legacy PDF document collections that were created before the possibility of integrating hyperlinks into documents was ever considered. To achieve our goal, we need to carry out two tasks: first, we need to identify and link citations and references in the text with high reliability; and second, we need the ability to determine physical PDF page locations for these elements. We demonstrate the use of a high-accuracy citation extraction algorithm which significantly improves on earlier reported techniques, and a technique for integrating PDF processing with a conventional text-stream based information extraction pipeline. We demonstrate these techniques in the context of a particular document collection, this being the ACL Anthology; but the same approach can be applied to other document sets.

  16. Face Contour Extraction of Information%人脸轮廓信息的提取

    Institute of Scientific and Technical Information of China (English)

    原瑾

    2011-01-01

    边缘提取在模式识别、机器视觉、图像分析及图像编码等领域都有着重要的研究价值。人脸检测技术是一种人脸识别技术的前提。文章针对人脸检测中人脸定位提出了人脸轮廓信息提取技术,确定人脸检测的主要区域。首先介绍了几种边缘检测算子,然后提出了动态阈值方法来改进图像阈值,提高了边缘检测精度。%Edge extraction has important research value in the fields of pattern recognition, machine vision, image analysis and image coding. Face detection technology is prerequisite of face recognition technology. In view of person face localization in person face detection, the dissertation proposes an extraction technology of face outline information to identify the main regional of face. This article first introduced several edge detection operators, and then proposed the method of dynamic threshold value to improves the image threshold value, which increased the edge detection accuracy.

  17. Metaproteomics: extracting and mining proteome information to characterize metabolic activities in microbial communities.

    Science.gov (United States)

    Abraham, Paul E; Giannone, Richard J; Xiong, Weili; Hettich, Robert L

    2014-06-17

    Contemporary microbial ecology studies usually employ one or more "omics" approaches to investigate the structure and function of microbial communities. Among these, metaproteomics aims to characterize the metabolic activities of the microbial membership, providing a direct link between the genetic potential and functional metabolism. The successful deployment of metaproteomics research depends on the integration of high-quality experimental and bioinformatic techniques for uncovering the metabolic activities of a microbial community in a way that is complementary to other "meta-omic" approaches. The essential, quality-defining informatics steps in metaproteomics investigations are: (1) construction of the metagenome, (2) functional annotation of predicted protein-coding genes, (3) protein database searching, (4) protein inference, and (5) extraction of metabolic information. In this article, we provide an overview of current bioinformatic approaches and software implementations in metaproteome studies in order to highlight the key considerations needed for successful implementation of this powerful community-biology tool.

  18. Optimal Extraction of Cosmological Information from Supernova Datain the Presence of Calibration Uncertainties

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Alex G.; Miquel, Ramon

    2005-09-26

    We present a new technique to extract the cosmological information from high-redshift supernova data in the presence of calibration errors and extinction due to dust. While in the traditional technique the distance modulus of each supernova is determined separately, in our approach we determine all distance moduli at once, in a process that achieves a significant degree of self-calibration. The result is a much reduced sensitivity of the cosmological parameters to the calibration uncertainties. As an example, for a strawman mission similar to that outlined in the SNAP satellite proposal, the increased precision obtained with the new approach is roughly equivalent to a factor of five decrease in the calibration uncertainty.

  19. Metaproteomics: extracting and mining proteome information to characterize metabolic activities in microbial communities

    Energy Technology Data Exchange (ETDEWEB)

    Abraham, Paul E [ORNL; Giannone, Richard J [ORNL; Xiong, Weili [ORNL; Hettich, Robert {Bob} L [ORNL

    2014-01-01

    Contemporary microbial ecology studies usually employ one or more omics approaches to investigate the structure and function of microbial communities. Among these, metaproteomics aims to characterize the metabolic activities of the microbial membership, providing a direct link between the genetic potential and functional metabolism. The successful deployment of metaproteomics research depends on the integration of high-quality experimental and bioinformatic techniques for uncovering the metabolic activities of a microbial community in a way that is complementary to other meta-omic approaches. The essential, quality-defining informatics steps in metaproteomics investigations are: (1) construction of the metagenome, (2) functional annotation of predicted protein-coding genes, (3) protein database searching, (4) protein inference, and (5) extraction of metabolic information. In this article, we provide an overview of current bioinformatic approaches and software implementations in metaproteome studies in order to highlight the key considerations needed for successful implementation of this powerful community-biology tool.

  20. EnvMine: A text-mining system for the automatic extraction of contextual information

    Directory of Open Access Journals (Sweden)

    de Lorenzo Victor

    2010-06-01

    Full Text Available Abstract Background For ecological studies, it is crucial to count on adequate descriptions of the environments and samples being studied. Such a description must be done in terms of their physicochemical characteristics, allowing a direct comparison between different environments that would be difficult to do otherwise. Also the characterization must include the precise geographical location, to make possible the study of geographical distributions and biogeographical patterns. Currently, there is no schema for annotating these environmental features, and these data have to be extracted from textual sources (published articles. So far, this had to be performed by manual inspection of the corresponding documents. To facilitate this task, we have developed EnvMine, a set of text-mining tools devoted to retrieve contextual information (physicochemical variables and geographical locations from textual sources of any kind. Results EnvMine is capable of retrieving the physicochemical variables cited in the text, by means of the accurate identification of their associated units of measurement. In this task, the system achieves a recall (percentage of items retrieved of 92% with less than 1% error. Also a Bayesian classifier was tested for distinguishing parts of the text describing environmental characteristics from others dealing with, for instance, experimental settings. Regarding the identification of geographical locations, the system takes advantage of existing databases such as GeoNames to achieve 86% recall with 92% precision. The identification of a location includes also the determination of its exact coordinates (latitude and longitude, thus allowing the calculation of distance between the individual locations. Conclusion EnvMine is a very efficient method for extracting contextual information from different text sources, like published articles or web pages. This tool can help in determining the precise location and physicochemical

  1. Intelligent information extraction to aid science decision making in autonomous space exploration

    Science.gov (United States)

    Merényi, Erzsébet; Tasdemir, Kadim; Farrand, William H.

    2008-04-01

    Effective scientific exploration of remote targets such as solar system objects increasingly calls for autonomous data analysis and decision making on-board. Today, robots in space missions are programmed to traverse from one location to another without regard to what they might be passing by. By not processing data as they travel, they can miss important discoveries, or will need to travel back if scientists on Earth find the data warrant backtracking. This is a suboptimal use of resources even on relatively close targets such as the Moon or Mars. The farther mankind ventures into space, the longer the delay in communication, due to which interesting findings from data sent back to Earth are made too late to command a (roving, floating, or orbiting) robot to further examine a given location. However, autonomous commanding of robots in scientific exploration can only be as reliable as the scientific information extracted from the data that is collected and provided for decision making. In this paper, we focus on the discovery scenario, where information extraction is accomplished with unsupervised clustering. For high-dimensional data with complicated structure, detailed segmentation that identifies all significant groups and discovers the small, surprising anomalies in the data, is a challenging task at which conventional algorithms often fail. We approach the problem with precision manifold learning using self-organizing neural maps with non-standard features developed in the course of our research. We demonstrate the effectiveness and robustness of this approach on multi-spectral imagery from the Mars Exploration Rovers Pancam, and on synthetic hyperspectral imagery.

  2. Classification and prioritization of biomedical literature for the comparative toxicogenomics database.

    Science.gov (United States)

    Vishnyakova, Dina; Pasche, Emilie; Gobeill, Julien; Gaudinat, Arnaud; Lovis, Christian; Ruch, Patrick

    2012-01-01

    We present a new approach to perform biomedical documents classification and prioritization for the Comparative Toxicogenomics Database (CTD). This approach is motivated by needs such as literature curation, in particular applied to the human health environment domain. The unique integration of chemical, genes/proteins and disease data in the biomedical literature may advance the identification of exposure and disease biomarkers, mechanisms of chemical actions, and the complex aetiologies of chronic diseases. Our approach aims to assist biomedical researchers when searching for relevant articles for CTD. The task is functionally defined as a binary classification task, where selected articles must also be ranked by order of relevance. We design a SVM classifier, which combines three main feature sets: an information retrieval system (EAGLi), a biomedical named-entity recognizer (MeSH term extraction), a gene normalization (GN) service (NormaGene) and an ad-hoc keyword recognizer for diseases and chemicals. The evaluation of the gene identification module was done on BioCreativeIII test data. Disease normalization is achieved with 95% precision and 93% of recall. The evaluation of the classification was done on the corpus provided by BioCreative organizers in 2012. The approach showed promising performance on the test data.

  3. Biomedical enhancements as justice.

    Science.gov (United States)

    Nam, Jeesoo

    2015-02-01

    Biomedical enhancements, the applications of medical technology to make better those who are neither ill nor deficient, have made great strides in the past few decades. Using Amartya Sen's capability approach as my framework, I argue in this article that far from being simply permissible, we have a prima facie moral obligation to use these new developments for the end goal of promoting social justice. In terms of both range and magnitude, the use of biomedical enhancements will mark a radical advance in how we compensate the most disadvantaged members of society.

  4. Advances in biomedical engineering

    CERN Document Server

    Brown, J H U

    1976-01-01

    Advances in Biomedical Engineering, Volume 6, is a collection of papers that discusses the role of integrated electronics in medical systems and the usage of biological mathematical models in biological systems. Other papers deal with the health care systems, the problems and methods of approach toward rehabilitation, as well as the future of biomedical engineering. One paper discusses the use of system identification as it applies to biological systems to estimate the values of a number of parameters (for example, resistance, diffusion coefficients) by indirect means. More particularly, the i

  5. Advances in biomedical engineering

    CERN Document Server

    Brown, J H U

    1976-01-01

    Advances in Biomedical Engineering, Volume 5, is a collection of papers that deals with application of the principles and practices of engineering to basic and applied biomedical research, development, and the delivery of health care. The papers also describe breakthroughs in health improvements, as well as basic research that have been accomplished through clinical applications. One paper examines engineering principles and practices that can be applied in developing therapeutic systems by a controlled delivery system in drug dosage. Another paper examines the physiological and materials vari

  6. Biomedical implantable microelectronics.

    Science.gov (United States)

    Meindl, J D

    1980-10-17

    Innovative applications of microelectronics in new biomedical implantable instruments offer a singular opportunity for advances in medical research and practice because of two salient factors: (i) beyond all other types of biomedical instruments, implants exploit fully the inherent technical advantages--complex functional capability, high reliability, lower power drain, small size and weight-of microelectronics, and (ii) implants bring microelectronics into intimate association with biological systems. The combination of these two factors enables otherwise impossible new experiments to be conducted and new paostheses developed that will improve the quality of human life.

  7. Ethics in biomedical engineering.

    Science.gov (United States)

    Morsy, Ahmed; Flexman, Jennifer

    2008-01-01

    This session focuses on a number of aspects of the subject of Ethics in Biomedical Engineering. The session starts by providing a case study of a company that manufactures artificial heart valves where the valves were failing at an unexpected rate. The case study focuses on Biomedical Engineers working at the company and how their education and training did not prepare them to deal properly with such situation. The second part of the session highlights the need to learn about various ethics rules and policies regulating research involving human or animal subjects.

  8. Capturing the Value of Biomedical Research.

    Science.gov (United States)

    Bertuzzi, Stefano; Jamaleddine, Zeina

    2016-03-24

    Assessing the real-world impact of biomedical research is notoriously difficult. Here, we present the framework for building a prospective science-centered information system from scratch that has been afforded by the Sidra Medical and Research Center in Qatar. This experiment is part of the global conversation on maximizing returns on research investment.

  9. Status of Research in Biomedical Engineering 1968.

    Science.gov (United States)

    National Inst. of General Medical Sciences (NIH), Bethesda, MD.

    This status report is divided into eight sections. The first four represent the classical engineering or building aspects of bioengineering and deal with biomedical instrumentation, prosthetics, man-machine systems and computer and information systems. The next three sections are related to the scientific, intellectual and academic influence of…

  10. Information Management Processes for Extraction of Student Dropout Indicators in Courses in Distance Mode

    Directory of Open Access Journals (Sweden)

    Renata Maria Abrantes Baracho

    2016-04-01

    Full Text Available This research addresses the use of information management processes in order to extract student dropout indicators in distance mode courses. Distance education in Brazil aims to facilitate access to information. The MEC (Ministry of Education announced, in the second semester of 2013, that the main obstacles faced by institutions offering courses in this mode were students dropping out and the resistance of both educators and students to this mode. The research used a mixed methodology, qualitative and quantitative, to obtain student dropout indicators. The factors found and validated in this research were: the lack of interest from students, insufficient training in the use of the virtual learning environment for students, structural problems in the schools that were chosen to offer the course, students without e-mail, incoherent answers to activities to the course, lack of knowledge on the part of the student when using the computer tool. The scenario considered was a course offered in distance mode called Aluno Integrado (Integrated Student

  11. A methodology for the extraction of quantitative information from electron microscopy images at the atomic level

    Science.gov (United States)

    Galindo, P. L.; Pizarro, J.; Guerrero, E.; Guerrero-Lebrero, M. P.; Scavello, G.; Yáñez, A.; Núñez-Moraleda, B. M.; Maestre, J. M.; Sales, D. L.; Herrera, M.; Molina, S. I.

    2014-06-01

    In this paper we describe a methodology developed at the University of Cadiz (Spain) in the past few years for the extraction of quantitative information from electron microscopy images at the atomic level. This work is based on a coordinated and synergic activity of several research groups that have been working together over the last decade in two different and complementary fields: Materials Science and Computer Science. The aim of our joint research has been to develop innovative high-performance computing techniques and simulation methods in order to address computationally challenging problems in the analysis, modelling and simulation of materials at the atomic scale, providing significant advances with respect to existing techniques. The methodology involves several fundamental areas of research including the analysis of high resolution electron microscopy images, materials modelling, image simulation and 3D reconstruction using quantitative information from experimental images. These techniques for the analysis, modelling and simulation allow optimizing the control and functionality of devices developed using materials under study, and have been tested using data obtained from experimental samples.

  12. A comparison of techniques for extracting emissivity information from thermal infrared data for geologic studies

    Science.gov (United States)

    Hook, Simon J.; Gabell, A. R.; Green, A. A.; Kealy, P. S.

    1992-01-01

    This article evaluates three techniques developed to extract emissivity information from multispectral thermal infrared data. The techniques are the assumed Channel 6 emittance model, thermal log residuals, and alpha residuals. These techniques were applied to calibrated, atmospherically corrected thermal infrared multispectral scanner (TIMS) data acquired over Cuprite, Nevada in September 1990. Results indicate that the two new techniques (thermal log residuals and alpha residuals) provide two distinct advantages over the assumed Channel 6 emittance model. First, they permit emissivity information to be derived from all six TIMS channels. The assumed Channel 6 emittance model only permits emissivity values to be derived from five of the six TIMS channels. Second, both techniques are less susceptible to noise than the assumed Channel 6 emittance model. The disadvantage of both techniques is that laboratory data must be converted to thermal log residuals or alpha residuals to facilitate comparison with similarly processed image data. An additional advantage of the alpha residual technique is that the processed data are scene-independent unlike those obtained with the other techniques.

  13. Should biomedical research be like Airbnb?

    Science.gov (United States)

    Bonazzi, Vivien R; Bourne, Philip E

    2017-04-01

    The thesis presented here is that biomedical research is based on the trusted exchange of services. That exchange would be conducted more efficiently if the trusted software platforms to exchange those services, if they exist, were more integrated. While simpler and narrower in scope than the services governing biomedical research, comparison to existing internet-based platforms, like Airbnb, can be informative. We illustrate how the analogy to internet-based platforms works and does not work and introduce The Commons, under active development at the National Institutes of Health (NIH) and elsewhere, as an example of the move towards platforms for research.

  14. Chitosan: A Promising Marine Polysaccharide for Biomedical Research.

    Science.gov (United States)

    Periayah, Mercy Halleluyah; Halim, Ahmad Sukari; Saad, Arman Zaharil Mat

    2016-01-01

    Biomaterials created 50 years ago are still receiving considerable attention for their potential to support development in the biomedical field. Diverse naturally obtained polysaccharides supply a broad range of resources applicable in the biomedical field. Lately, chitosan, a marine polysaccharide derived from chitins-which are extracted from the shells of arthropods such as crab, shrimp, and lobster-is becoming the most wanted biopolymer for use toward therapeutic interventions. This is a general short review of chitosan, highlighting the history, properties, chemical structure, processing method, and factors influencing the usage of chitosan derivatives in the biomedical field.

  15. Chitosan: A promising marine polysaccharide for biomedical research

    Directory of Open Access Journals (Sweden)

    Mercy Halleluyah Periayah

    2016-01-01

    Full Text Available Biomaterials created 50 years ago are still receiving considerable attention for their potential to support development in the biomedical field. Diverse naturally obtained polysaccharides supply a broad range of resources applicable in the biomedical field. Lately, chitosan, a marine polysaccharide derived from chitins—which are extracted from the shells of arthropods such as crab, shrimp, and lobster—is becoming the most wanted biopolymer for use toward therapeutic interventions. This is a general short review of chitosan, highlighting the history, properties, chemical structure, processing method, and factors influencing the usage of chitosan derivatives in the biomedical field.

  16. Marine Collagen: An Emerging Player in Biomedical applications

    OpenAIRE

    Subhan, Fazli; Ikram, Muhammad; Shehzad,Adeeb; Ghafoor, Abdul

    2014-01-01

    Mammalian collagen is a multifactorial biomaterial that is widely used for beneficial purposes in the advanced biomedical technologies. Generally, biomedical applicable collagen is extracted from the mammalian body, but it can also be derived from marine species. Recently, mammalian tissues collagen proteins are considered a great pathological risk for transmitted diseases, because purification of such protein is very challenging and needs efficient tool to avoid structure alteration. Thus, d...

  17. A re-evaluation of biomedical named entity-term relations.

    Science.gov (United States)

    Ohta, Tomoko; Pyysalo, Sampo; Kim, Jin-Dong; Tsujii, Jun'ichi

    2010-10-01

    Text mining can support the interpretation of the enormous quantity of textual data produced in biomedical field. Recent developments in biomedical text mining include advances in the reliability of the recognition of named entities (NEs) such as specific genes and proteins, as well as movement toward richer representations of the associations of NEs. We argue that this shift in representation should be accompanied by the adoption of a more detailed model of the relations holding between NEs and other relevant domain terms. As a step toward this goal, we study NE-term relations with the aim of defining a detailed, broadly applicable set of relation types based on accepted domain standard concepts for use in corpus annotation and domain information extraction approaches.

  18. Malleable Fuzzy Local Median C Means Algorithm for Effective Biomedical Image Segmentation

    Science.gov (United States)

    Rajendran, Arunkumar; Balakrishnan, Nagaraj; Varatharaj, Mithya

    2016-12-01

    The traditional way of clustering plays an effective role in the field of segmentation which was developed to be more effective and also in the recent development the extraction of contextual information can be processed with ease. This paper presents a modified Fuzzy C-Means (FCM) algorithm that provides the better segmentation in the contour grayscale regions of the biomedical images where effective cluster is needed. Malleable Fuzzy Local Median C-Means (M-FLMCM) is the proposed algorithm, proposed to overcome the disadvantage of the traditional FCM method in which the convergence time requirement is more, lack of ability to remove the noise, and the inability to cluster the contour region such as images. M-FLMCM shows promising results in the experiment with real-world biomedical images. The experiment results, with 96 % accuracy compared to the other algorithms.

  19. An Unsupervised Graph Based Continuous Word Representation Method for Biomedical Text Mining.

    Science.gov (United States)

    Jiang, Zhenchao; Li, Lishuang; Huang, Degen

    2016-01-01

    In biomedical text mining tasks, distributed word representation has succeeded in capturing semantic regularities, but most of them are shallow-window based models, which are not sufficient for expressing the meaning of words. To represent words using deeper information, we make explicit the semantic regularity to emerge in word relations, including dependency relations and context relations, and propose a novel architecture for computing continuous vector representation by leveraging those relations. The performance of our model is measured on word analogy task and Protein-Protein Interaction Extraction (PPIE) task. Experimental results show that our method performs overall better than other word representation models on word analogy task and have many advantages on biomedical text mining.

  20. Biomedical Engineering in Modern Society

    Science.gov (United States)

    Attinger, E. O.

    1971-01-01

    Considers definition of biomedical engineering (BME) and how biomedical engineers should be trained. State of the art descriptions of BME and BME education are followed by a brief look at the future of BME. (TS)

  1. Anatomy for Biomedical Engineers

    Science.gov (United States)

    Carmichael, Stephen W.; Robb, Richard A.

    2008-01-01

    There is a perceived need for anatomy instruction for graduate students enrolled in a biomedical engineering program. This appeared especially important for students interested in and using medical images. These students typically did not have a strong background in biology. The authors arranged for students to dissect regions of the body that…

  2. NASA Biomedical Informatics Capabilities and Needs

    Science.gov (United States)

    Johnson-Throop, Kathy A.

    2009-01-01

    To improve on-orbit clinical capabilities by developing and providing operational support for intelligent, robust, reliable, and secure, enterprise-wide and comprehensive health care and biomedical informatics systems with increasing levels of autonomy, for use on Earth, low Earth orbit & exploration class missions. Biomedical Informatics is an emerging discipline that has been defined as the study, invention, and implementation of structures and algorithms to improve communication, understanding and management of medical information. The end objective of biomedical informatics is the coalescing of data, knowledge, and the tools necessary to apply that data and knowledge in the decision-making process, at the time and place that a decision needs to be made.

  3. Information Extraction and Dependency on Open Government Data (ogd) for Environmental Monitoring

    Science.gov (United States)

    Abdulmuttalib, Hussein

    2016-06-01

    Environmental monitoring practices support decision makers of different government / private institutions, besides environmentalists and planners among others. This support helps them act towards the sustainability of our environment, and also take efficient measures for protecting human beings in general, but it is difficult to explore useful information from 'OGD' and assure its quality for the purpose. On the other hand, Monitoring itself comprises detecting changes as happens, or within the mitigation period range, which means that any source of data, that is to be used for monitoring, should replicate the information related to the period of environmental monitoring, or otherwise it's considered almost useless or history. In this paper the assessment of information extraction and structuring from Open Government Data 'OGD', that can be useful to environmental monitoring is performed, looking into availability, usefulness to environmental monitoring of a certain type, checking its repetition period and dependences. The particular assessment is being performed on a small sample selected from OGD, bearing in mind the type of the environmental change monitored, such as the increase and concentrations of built up areas, and reduction of green areas, or monitoring the change of temperature in a specific area. The World Bank mentioned in its blog that Data is open if it satisfies both conditions of, being technically open, and legally open. The use of Open Data thus, is regulated by published terms of use, or an agreement which implies some conditions without violating the above mentioned two conditions. Within the scope of the paper I wish to share the experience of using some OGD for supporting an environmental monitoring work, that is performed to mitigate the production of carbon dioxide, by regulating energy consumption, and by properly designing the test area's landscapes, thus using Geodesign tactics, meanwhile wish to add to the results achieved by many

  4. Urban Built-Up Area Extraction from Landsat TM/ETM+ Images Using Spectral Information and Multivariate Texture

    Directory of Open Access Journals (Sweden)

    Jun Zhang

    2014-08-01

    Full Text Available Urban built-up area information is required by various applications. However, urban built-up area extraction using moderate resolution satellite data, such as Landsat series data, is still a challenging task due to significant intra-urban heterogeneity and spectral confusion with other land cover types. In this paper, a new method that combines spectral information and multivariate texture is proposed. The multivariate textures are separately extracted from multispectral data using a multivariate variogram with different distance measures, i.e., Euclidean, Mahalanobis and spectral angle distances. The multivariate textures and the spectral bands are then combined for urban built-up area extraction. Because the urban built-up area is the only target class, a one-class classifier, one-class support vector machine, is used. For comparison, the classical gray-level co-occurrence matrix (GLCM is also used to extract image texture. The proposed method was evaluated using bi-temporal Landsat TM/ETM+ data of two megacity areas in China. Results demonstrated that the proposed method outperformed the use of spectral information alone and the joint use of the spectral information and the GLCM texture. In particular, the inclusion of multivariate variogram textures with spectral angle distance achieved the best results. The proposed method provides an effective way of extracting urban built-up areas from Landsat series images and could be applicable to other applications.

  5. Annotating image ROIs with text descriptions for multimodal biomedical document retrieval

    Science.gov (United States)

    You, Daekeun; Simpson, Matthew; Antani, Sameer; Demner-Fushman, Dina; Thoma, George R.

    2013-01-01

    Regions of interest (ROIs) that are pointed to by overlaid markers (arrows, asterisks, etc.) in biomedical images are expected to contain more important and relevant information than other regions for biomedical article indexing and retrieval. We have developed several algorithms that localize and extract the ROIs by recognizing markers on images. Cropped ROIs then need to be annotated with contents describing them best. In most cases accurate textual descriptions of the ROIs can be found from figure captions, and these need to be combined with image ROIs for annotation. The annotated ROIs can then be used to, for example, train classifiers that separate ROIs into known categories (medical concepts), or to build visual ontologies, for indexing and retrieval of biomedical articles. We propose an algorithm that pairs visual and textual ROIs that are extracted from images and figure captions, respectively. This algorithm based on dynamic time warping (DTW) clusters recognized pointers into groups, each of which contains pointers with identical visual properties (shape, size, color, etc.). Then a rule-based matching algorithm finds the best matching group for each textual ROI mention. Our method yields a precision and recall of 96% and 79%, respectively, when ground truth textual ROI data is used.

  6. Discovering gene annotations in biomedical text databases

    Directory of Open Access Journals (Sweden)

    Ozsoyoglu Gultekin

    2008-03-01

    Full Text Available Abstract Background Genes and gene products are frequently annotated with Gene Ontology concepts based on the evidence provided in genomics articles. Manually locating and curating information about a genomic entity from the biomedical literature requires vast amounts of human effort. Hence, there is clearly a need forautomated computational tools to annotate the genes and gene products with Gene Ontology concepts by computationally capturing the related knowledge embedded in textual data. Results In this article, we present an automated genomic entity annotation system, GEANN, which extracts information about the characteristics of genes and gene products in article abstracts from PubMed, and translates the discoveredknowledge into Gene Ontology (GO concepts, a widely-used standardized vocabulary of genomic traits. GEANN utilizes textual "extraction patterns", and a semantic matching framework to locate phrases matching to a pattern and produce Gene Ontology annotations for genes and gene products. In our experiments, GEANN has reached to the precision level of 78% at therecall level of 61%. On a select set of Gene Ontology concepts, GEANN either outperforms or is comparable to two other automated annotation studies. Use of WordNet for semantic pattern matching improves the precision and recall by 24% and 15%, respectively, and the improvement due to semantic pattern matching becomes more apparent as the Gene Ontology terms become more general. Conclusion GEANN is useful for two distinct purposes: (i automating the annotation of genomic entities with Gene Ontology concepts, and (ii providing existing annotations with additional "evidence articles" from the literature. The use of textual extraction patterns that are constructed based on the existing annotations achieve high precision. The semantic pattern matching framework provides a more flexible pattern matching scheme with respect to "exactmatching" with the advantage of locating approximate

  7. Biomedical signals, imaging, and informatics

    CERN Document Server

    Bronzino, Joseph D

    2014-01-01

    Known as the bible of biomedical engineering, The Biomedical Engineering Handbook, Fourth Edition, sets the standard against which all other references of this nature are measured. As such, it has served as a major resource for both skilled professionals and novices to biomedical engineering.Biomedical Signals, Imaging, and Informatics, the third volume of the handbook, presents material from respected scientists with diverse backgrounds in biosignal processing, medical imaging, infrared imaging, and medical informatics.More than three dozen specific topics are examined, including biomedical s

  8. Feature Extraction and Selection Scheme for Intelligent Engine Fault Diagnosis Based on 2DNMF, Mutual Information, and NSGA-II

    Directory of Open Access Journals (Sweden)

    Peng-yuan Liu

    2016-01-01

    Full Text Available A novel feature extraction and selection scheme is presented for intelligent engine fault diagnosis by utilizing two-dimensional nonnegative matrix factorization (2DNMF, mutual information, and nondominated sorting genetic algorithms II (NSGA-II. Experiments are conducted on an engine test rig, in which eight different engine operating conditions including one normal condition and seven fault conditions are simulated, to evaluate the presented feature extraction and selection scheme. In the phase of feature extraction, the S transform technique is firstly utilized to convert the engine vibration signals to time-frequency domain, which can provide richer information on engine operating conditions. Then a novel feature extraction technique, named two-dimensional nonnegative matrix factorization, is employed for characterizing the time-frequency representations. In the feature selection phase, a hybrid filter and wrapper scheme based on mutual information and NSGA-II is utilized to acquire a compact feature subset for engine fault diagnosis. Experimental results by adopted three different classifiers have demonstrated that the proposed feature extraction and selection scheme can achieve a very satisfying classification performance with fewer features for engine fault diagnosis.

  9. Extracting conformational structure information of benzene molecules via laser-induced electron diffraction

    Directory of Open Access Journals (Sweden)

    Yuta Ito

    2016-05-01

    Full Text Available We have measured the angular distributions of high energy photoelectrons of benzene molecules generated by intense infrared femtosecond laser pulses. These electrons arise from the elastic collisions between the benzene ions with the previously tunnel-ionized electrons that have been driven back by the laser field. Theory shows that laser-free elastic differential cross sections (DCSs can be extracted from these photoelectrons, and the DCS can be used to retrieve the bond lengths of gas-phase molecules similar to the conventional electron diffraction method. From our experimental results, we have obtained the C-C and C-H bond lengths of benzene with a spatial resolution of about 10 pm. Our results demonstrate that laser induced electron diffraction (LIED experiments can be carried out with the present-day ultrafast intense lasers already. Looking ahead, with aligned or oriented molecules, more complete spatial information of the molecule can be obtained from LIED, and applying LIED to probe photo-excited molecules, a “molecular movie” of the dynamic system may be created with sub-Ångström spatial and few-ten femtosecond temporal resolutions.

  10. Extracting structural information from the polarization dependence of one- and two-dimensional sum frequency generation spectra.

    Science.gov (United States)

    Laaser, Jennifer E; Zanni, Martin T

    2013-07-25

    We present ways in which pulse sequences and polarizations can be used to extract structural information from one- and two-dimensional vibrational sum frequency generation (2D SFG) spectra. We derive analytic expressions for the polarization dependence of systems containing coupled vibrational modes, and we present simulated spectra to identify the features of different molecular geometries. We discuss several useful polarization combinations for suppressing strong diagonal peaks and emphasizing weaker cross-peaks. We investigate unique capabilities of 2D SFG spectra for obtaining structural information about SFG-inactive modes and for identifying coupled achiral chromophores. This work builds on techniques that have been developed for extracting structural information from 2D IR spectra. This paper discusses how to utilize these concepts in 2D SFG experiments to probe multioscillator systems at interfaces. The sample code for calculating polarization dependence of 1D and 2D SFG spectra is provided in the Supporting Information .

  11. Analysis Methods for Extracting Knowledge from Large-Scale WiFi Monitoring to Inform Building Facility Planning

    DEFF Research Database (Denmark)

    Ruiz-Ruiz, Antonio; Blunck, Henrik; Prentow, Thor Siiger;

    2014-01-01

    realistic data to inform facility planning. In this paper, we propose analysis methods to extract knowledge from large sets of network collected WiFi traces to better inform facility management and planning in large building complexes. The analysis methods, which build on a rich set of temporal and spatial....... Spatio-temporal visualization tools built on top of these methods enable planners to inspect and explore extracted information to inform facility-planning activities. To evaluate the methods, we present results for a large hospital complex covering more than 10 hectares. The evaluation is based on WiFi...... traces collected in the hospital’s WiFi infrastructure over two weeks observing around 18000 different devices recording more than a billion individual WiFi measurements. For the presented analysis methods we present quantitative performance results, e.g., demonstrating over 95% accuracy for correct...

  12. How are medical students trained to locate biomedical information to practice evidence-based medicine? a review of the 2007–2012 literature

    Science.gov (United States)

    Maggio, Lauren A.; Kung, Janice Y.

    2014-01-01

    Objectives: This study describes how information retrieval skills are taught in evidence-based medicine (EBM) at the undergraduate medical education (UGME) level. Methods: The authors systematically searched MEDLINE, Scopus, Educational Resource Information Center, Web of Science, and Evidence-Based Medicine Reviews for English-language articles published between 2007 and 2012 describing information retrieval training to support EBM. Data on learning environment, frequency of training, learner characteristics, resources and information skills taught, teaching modalities, and instructor roles were compiled and analyzed. Results: Twelve studies were identified for analysis. Studies were set in the United States (9), Australia (1), the Czech Republic (1), and Iran (1). Most trainings (7) featured multiple sessions with trainings offered to preclinical students (5) and clinical students (6). A single study described a longitudinal training experience. A variety of information resources were introduced, including PubMed, DynaMed, UpToDate, and AccessMedicine. The majority of the interventions (10) were classified as interactive teaching sessions in classroom settings. Librarians played major and collaborative roles with physicians in teaching and designing training. Unfortunately, few studies provided details of information skills activities or evaluations, making them difficult to evaluate and replicate. Conclusions: This study reviewed the literature and characterized how EBM search skills are taught in UGME. Details are provided on learning environment, frequency of training, level of learners, resources and skills trained, and instructor roles. Implications: The results suggest a number of steps that librarians can take to improve information skills training including using a longitudinal approach, integrating consumer health resources, and developing robust assessments. PMID:25031559

  13. Recent Advances and Emerging Applications in Text and Data Mining for Biomedical Discovery.

    Science.gov (United States)

    Gonzalez, Graciela H; Tahsin, Tasnia; Goodale, Britton C; Greene, Anna C; Greene, Casey S

    2016-01-01

    Precision medicine will revolutionize the way we treat and prevent disease. A major barrier to the implementation of precision medicine that clinicians and translational scientists face is understanding the underlying mechanisms of disease. We are starting to address this challenge through automatic approaches for information extraction, representation and analysis. Recent advances in text and data mining have been applied to a broad spectrum of key biomedical questions in genomics, pharmacogenomics and other fields. We present an overview of the fundamental methods for text and data mining, as well as recent advances and emerging applications toward precision medicine.

  14. In-shore ship extraction from HR optical remote sensing image via salience structure and GIS information

    Science.gov (United States)

    Ren, Xiaoyuan; Jiang, Libing; Tang, Xiao-an

    2015-12-01

    In order to solve the problem of in-shore ship extraction from remote sensing image, a novel method for in-shore ship extraction from high resolution (HR) optical remote sensing image is proposed via salience structure feature and GIS information. Firstly, the berth ROI is located in the image with the aid of the prior GIS auxiliary information. Secondly, the salient corner features at ship bow are extracted from the berth ROI precisely. Finally, a recursive algorithm concerning the symmetric geometry of the ship target is conducted to discriminate the multi docked in-shore targets into mono in-shore ships. The results of the experiments show that the method proposed in this paper can detect the majority of large and medium scale in-shore ships from the optical remote sensing image, including both the mono and the multi adjacent docked in-shore ship cases.

  15. Optical Polarizationin Biomedical Applications

    CERN Document Server

    Tuchin, Valery V; Zimnyakov, Dmitry A

    2006-01-01

    Optical Polarization in Biomedical Applications introduces key developments in optical polarization methods for quantitative studies of tissues, while presenting the theory of polarization transfer in a random medium as a basis for the quantitative description of polarized light interaction with tissues. This theory uses the modified transfer equation for Stokes parameters and predicts the polarization structure of multiple scattered optical fields. The backscattering polarization matrices (Jones matrix and Mueller matrix) important for noninvasive medical diagnostic are introduced. The text also describes a number of diagnostic techniques such as CW polarization imaging and spectroscopy, polarization microscopy and cytometry. As a new tool for medical diagnosis, optical coherent polarization tomography is analyzed. The monograph also covers a range of biomedical applications, among them cataract and glaucoma diagnostics, glucose sensing, and the detection of bacteria.

  16. Adaptive Biomedical Innovation.

    Science.gov (United States)

    Honig, P K; Hirsch, G

    2016-12-01

    Adaptive Biomedical Innovation (ABI) is a multistakeholder approach to product and process innovation aimed at accelerating the delivery of clinical value to patients and society. ABI offers the opportunity to transcend the fragmentation and linearity of decision-making in our current model and create a common collaborative framework that optimizes the benefit and access of new medicines for patients as well as creating a more sustainable innovation ecosystem.

  17. [Biomedical activity of biosurfactants].

    Science.gov (United States)

    Krasowska, Anna

    2010-07-23

    Biosurfactants, amphiphilic compounds, synthesized by microorganisms have surface, antimicrobial and antitumor properties. Biosurfactants prevent adhesion and biofilms formation by bacteria and fungi on various surfaces. For many years microbial surfactants are used as antibiotics with board spectrum of activity against microorganisms. Biosurfactants act as antiviral compounds and their antitumor activities are mediated through induction of apoptosis. This work presents the current state of knowledge related to biomedical activity of biosurfactants.

  18. Integrating image data into biomedical text categorization.

    Science.gov (United States)

    Shatkay, Hagit; Chen, Nawei; Blostein, Dorothea

    2006-07-15

    Categorization of biomedical articles is a central task for supporting various curation efforts. It can also form the basis for effective biomedical text mining. Automatic text classification in the biomedical domain is thus an active research area. Contests organized by the KDD Cup (2002) and the TREC Genomics track (since 2003) defined several annotation tasks that involved document classification, and provided training and test data sets. So far, these efforts focused on analyzing only the text content of documents. However, as was noted in the KDD'02 text mining contest-where figure-captions proved to be an invaluable feature for identifying documents of interest-images often provide curators with critical information. We examine the possibility of using information derived directly from image data, and of integrating it with text-based classification, for biomedical document categorization. We present a method for obtaining features from images and for using them-both alone and in combination with text-to perform the triage task introduced in the TREC Genomics track 2004. The task was to determine which documents are relevant to a given annotation task performed by the Mouse Genome Database curators. We show preliminary results, demonstrating that the method has a strong potential to enhance and complement traditional text-based categorization methods.

  19. Biomedical accelerator mass spectrometry

    Science.gov (United States)

    Freeman, Stewart P. H. T.; Vogel, John S.

    1995-05-01

    Ultrasensitive SIMS with accelerator based spectrometers has recently begun to be applied to biomedical problems. Certain very long-lived radioisotopes of very low natural abundances can be used to trace metabolism at environmental dose levels ( [greater-or-equal, slanted] z mol in mg samples). 14C in particular can be employed to label a myriad of compounds. Competing technologies typically require super environmental doses that can perturb the system under investigation, followed by uncertain extrapolation to the low dose regime. 41Ca and 26Al are also used as elemental tracers. Given the sensitivity of the accelerator method, care must be taken to avoid contamination of the mass spectrometer and the apparatus employed in prior sample handling including chemical separation. This infant field comprises the efforts of a dozen accelerator laboratories. The Center for Accelerator Mass Spectrometry has been particularly active. In addition to collaborating with groups further afield, we are researching the kinematics and binding of genotoxins in-house, and we support innovative uses of our capability in the disciplines of chemistry, pharmacology, nutrition and physiology within the University of California. The field can be expected to grow further given the numerous potential applications and the efforts of several groups and companies to integrate more the accelerator technology into biomedical research programs; the development of miniaturized accelerator systems and ion sources capable of interfacing to conventional HPLC and GMC, etc. apparatus for complementary chemical analysis is anticipated for biomedical laboratories.

  20. Wireless tuning fork gyroscope for biomedical applications

    Science.gov (United States)

    Abraham, Jose K.; Varadan, Vijay K.; Whitchurch, Ashwin K.; Sarukesi, K.

    2003-07-01

    This paper presents the development of a Bluetooth enabled wireless tuning fork gyroscope for the biomedical applications, including gait phase detection system, human motion analysis and physical therapy. This gyroscope is capable of measuring rotation rates between -90 and 90 and it can read the rotation information using a computer. Currently, the information from a gyroscope can trigger automobile airbag deployment during rollover, improve the accuracy and reliability of GPS navigation systems and stabilize moving platforms such as automobiles, airplanes, robots, antennas, and industrial equipment. Adding wireless capability to the existing gyroscope could help to expand its applications in many areas particularly in biomedical applications, where a continuous patient monitoring is quite difficult. This wireless system provides information on several aspects of activities of patients for real-time monitoring in hospitals.

  1. Biomedical Terminology Mapper for UML projects.

    Science.gov (United States)

    Thibault, Julien C; Frey, Lewis

    2013-01-01

    As the biomedical community collects and generates more and more data, the need to describe these datasets for exchange and interoperability becomes crucial. This paper presents a mapping algorithm that can help developers expose local implementations described with UML through standard terminologies. The input UML class or attribute name is first normalized and tokenized, then lookups in a UMLS-based dictionary are performed. For the evaluation of the algorithm 142 UML projects were extracted from caGrid and automatically mapped to National Cancer Institute (NCI) terminology concepts. Resulting mappings at the UML class and attribute levels were compared to the manually curated annotations provided in caGrid. Results are promising and show that this type of algorithm could speed-up the tedious process of mapping local implementations to standard biomedical terminologies.

  2. Facilitating biomedical researchers' interrogation of electronic health record data: Ideas from outside of biomedical informatics.

    Science.gov (United States)

    Hruby, Gregory W; Matsoukas, Konstantina; Cimino, James J; Weng, Chunhua

    2016-04-01

    Electronic health records (EHR) are a vital data resource for research uses, including cohort identification, phenotyping, pharmacovigilance, and public health surveillance. To realize the promise of EHR data for accelerating clinical research, it is imperative to enable efficient and autonomous EHR data interrogation by end users such as biomedical researchers. This paper surveys state-of-art approaches and key methodological considerations to this purpose. We adapted a previously published conceptual framework for interactive information retrieval, which defines three entities: user, channel, and source, by elaborating on channels for query formulation in the context of facilitating end users to interrogate EHR data. We show the current progress in biomedical informatics mainly lies in support for query execution and information modeling, primarily due to emphases on infrastructure development for data integration and data access via self-service query tools, but has neglected user support needed during iteratively query formulation processes, which can be costly and error-prone. In contrast, the information science literature has offered elaborate theories and methods for user modeling and query formulation support. The two bodies of literature are complementary, implying opportunities for cross-disciplinary idea exchange. On this basis, we outline the directions for future informatics research to improve our understanding of user needs and requirements for facilitating autonomous interrogation of EHR data by biomedical researchers. We suggest that cross-disciplinary translational research between biomedical informatics and information science can benefit our research in facilitating efficient data access in life sciences.

  3. NIH Funding for Biomedical Imaging

    Science.gov (United States)

    Conroy, Richard

    Biomedical imaging, and in particular MRI and CT, is often identified as among the top 10 most significant advances in healthcare in the 20th century. This presentation will describe some of the recent advances in medical physics and imaging being funded by NIH in this century and current funding opportunities. The presentation will also highlight the role of multidisciplinary research in bringing concepts from the physical sciences and applying them to challenges in biological and biomedical research.. NIH Funding for Biomedical Imaging.

  4. Enriching a biomedical event corpus with meta-knowledge annotation

    Directory of Open Access Journals (Sweden)

    Thompson Paul

    2011-10-01

    Full Text Available Abstract Background Biomedical papers contain rich information about entities, facts and events of biological relevance. To discover these automatically, we use text mining techniques, which rely on annotated corpora for training. In order to extract protein-protein interactions, genotype-phenotype/gene-disease associations, etc., we rely on event corpora that are annotated with classified, structured representations of important facts and findings contained within text. These provide an important resource for the training of domain-specific information extraction (IE systems, to facilitate semantic-based searching of documents. Correct interpretation of these events is not possible without additional information, e.g., does an event describe a fact, a hypothesis, an experimental result or an analysis of results? How confident is the author about the validity of her analyses? These and other types of information, which we collectively term meta-knowledge, can be derived from the context of the event. Results We have designed an annotation scheme for meta-knowledge enrichment of biomedical event corpora. The scheme is multi-dimensional, in that each event is annotated for 5 different aspects of meta-knowledge that can be derived from the textual context of the event. Textual clues used to determine the values are also annotated. The scheme is intended to be general enough to allow integration with different types of bio-event annotation, whilst being detailed enough to capture important subtleties in the nature of the meta-knowledge expressed in the text. We report here on both the main features of the annotation scheme, as well as its application to the GENIA event corpus (1000 abstracts with 36,858 events. High levels of inter-annotator agreement have been achieved, falling in the range of 0.84-0.93 Kappa. Conclusion By augmenting event annotations with meta-knowledge, more sophisticated IE systems can be trained, which allow interpretative

  5. Biomedical Sensors and Instruments

    CERN Document Server

    Tagawa, Tatsuo

    2011-01-01

    The living body is a difficult object to measure: accurate measurements of physiological signals require sensors and instruments capable of high specificity and selectivity that do not interfere with the systems under study. As a result, detailed knowledge of sensor and instrument properties is required to be able to select the "best" sensor from one of the many designed to meet these challenges. From the underlying principles to practical applications, this updated edition of Biomedical Sensors and Instruments provides an easy-to-understand introduction to the various kinds of biome

  6. Advances in biomedical engineering

    CERN Document Server

    Brown, J H U

    1973-01-01

    Advances in Biomedical Engineering, Volume 2, is a collection of papers that discusses the basic sciences, the applied sciences of engineering, the medical sciences, and the delivery of health services. One paper discusses the models of adrenal cortical control, including the secretion and metabolism of cortisol (the controlled process), as well as the initiation and modulation of secretion of ACTH (the controller). Another paper discusses hospital computer systems-application problems, objective evaluation of technology, and multiple pathways for future hospital computer applications. The pos

  7. Principles of Biomedical Engineering

    CERN Document Server

    Madihally, Sundararajan V

    2010-01-01

    Describing the role of engineering in medicine today, this comprehensive volume covers a wide range of the most important topics in this burgeoning field. Supported with over 145 illustrations, the book discusses bioelectrical systems, mechanical analysis of biological tissues and organs, biomaterial selection, compartmental modeling, and biomedical instrumentation. Moreover, you find a thorough treatment of the concept of using living cells in various therapeutics and diagnostics.Structured as a complete text for students with some engineering background, the book also makes a valuable refere

  8. Biomedical photonics handbook

    CERN Document Server

    Vo-Dinh, Tuan

    2003-01-01

    1.Biomedical Photonics: A Revolution at the Interface of Science and Technology, T. Vo-DinhPHOTONICS AND TISSUE OPTICS2.Optical Properties of Tissues, J. Mobley and T. Vo-Dinh3.Light-Tissue Interactions, V.V. Tuchin 4.Theoretical Models and Algorithms in Optical Diffusion Tomography, S.J. Norton and T. Vo-DinhPHOTONIC DEVICES5.Laser Light in Biomedicine and the Life Sciences: From the Present to the Future, V.S. Letokhov6.Basic Instrumentation in Photonics, T. Vo-Dinh7.Optical Fibers and Waveguides for Medical Applications, I. Gannot and

  9. Advances in biomedical engineering

    CERN Document Server

    Brown, J H U

    1973-01-01

    Advances in Biomedical Engineering, Volume 3, is a collection of papers that discusses circulatory system models, linguistics in computer usage, and clinical applications on patient monitoring. One paper describes the use of comparative models of overall circulatory mechanics that include models of the cardiac pump, of the vascular systems, and of the overall systems behavior. Another paper describes a model in processing medical language data that employs an explicit semantic structure, becoming the basis for the computer-based, artificial intelligence of the system. One paper cites studies b

  10. Advances in biomedical engineering

    CERN Document Server

    Brown, J H U

    1974-01-01

    Advances in Biomedical Engineering, Volume 4, is a collection of papers that deals with gas chromatography, mass spectroscopy and the analysis of minute samples, as well as the role of the government in regulating the production, usage, safety, and efficacy of medical devices. One paper reviews the use of mass spectrometry and computer technology in relation to gas-phase analytical methods based on gas chromatograph-mass spectrometer instruments and gas chromatograph-mass spectrometer-computer analytical systems. Many health practitioners, government and private health agencies, the legal prof

  11. Biomedical signals and systems

    CERN Document Server

    Tranquillo, Joseph V

    2013-01-01

    Biomedical Signals and Systems is meant to accompany a one-semester undergraduate signals and systems course. It may also serve as a quick-start for graduate students or faculty interested in how signals and systems techniques can be applied to living systems. The biological nature of the examples allows for systems thinking to be applied to electrical, mechanical, fluid, chemical, thermal and even optical systems. Each chapter focuses on a topic from classic signals and systems theory: System block diagrams, mathematical models, transforms, stability, feedback, system response, control, time

  12. Statistics in biomedical research

    Directory of Open Access Journals (Sweden)

    González-Manteiga, Wenceslao

    2007-06-01

    Full Text Available The discipline of biostatistics is nowadays a fundamental scientific component of biomedical, public health and health services research. Traditional and emerging areas of application include clinical trials research, observational studies, physiology, imaging, and genomics. The present article reviews the current situation of biostatistics, considering the statistical methods traditionally used in biomedical research, as well as the ongoing development of new methods in response to the new problems arising in medicine. Clearly, the successful application of statistics in biomedical research requires appropriate training of biostatisticians. This training should aim to give due consideration to emerging new areas of statistics, while at the same time retaining full coverage of the fundamentals of statistical theory and methodology. In addition, it is important that students of biostatistics receive formal training in relevant biomedical disciplines, such as epidemiology, clinical trials, molecular biology, genetics, and neuroscience.La Bioestadística es hoy en día una componente científica fundamental de la investigación en Biomedicina, salud pública y servicios de salud. Las áreas tradicionales y emergentes de aplicación incluyen ensayos clínicos, estudios observacionales, fisología, imágenes, y genómica. Este artículo repasa la situación actual de la Bioestadística, considerando los métodos estadísticos usados tradicionalmente en investigación biomédica, así como los recientes desarrollos de nuevos métodos, para dar respuesta a los nuevos problemas que surgen en Medicina. Obviamente, la aplicación fructífera de la estadística en investigación biomédica exige una formación adecuada de los bioestadísticos, formación que debería tener en cuenta las áreas emergentes en estadística, cubriendo al mismo tiempo los fundamentos de la teoría estadística y su metodología. Es importante, además, que los estudiantes de

  13. Biomedical problems of hydrotechnical construction

    Energy Technology Data Exchange (ETDEWEB)

    Avakyan, A.B.; El' piner, L.I.; Delitsyn, V.M.

    1988-04-01

    The effect of hydrotechnical and water-management construction on the living conditions and health of the population was examined. The results were used to develop the scientific bases and methods of biomedical predictions in several stages: evaluating biomedical conditions in territories where a change is expected, and constructing biomedical prediction proper of the effect of hydrotechnical constructions. The development of the indicated predictions make it possible to include measures on intensifying the positive and preventing or abating undesired effects on the biomedical situation when designing hydrotechnical and water-management construction.

  14. Biomedical publishing and the internet: evolution or revolution?

    Science.gov (United States)

    Jacobson, M W

    2000-01-01

    The Internet is challenging traditional publishing patterns. In the biomedical domain, medical journals are providing more and more content online, both free and for a fee. Beyond this, however, a number of commentators believe that traditional notions of copyright and intellectual property ownership are no longer suited to the information age and that ownership of copyright to research reports should be and will be wrested from publishers and returned to authors. In this paper, it is argued that, although the Internet will indeed profoundly affect the distribution of biomedical research results, the biomedical publishing industry is too intertwined with the research establishment and too powerful to fall prey to such a copyright revolution.

  15. A COMPARATIVE ANALYSIS OF WEB INFORMATION EXTRACTION TECHNIQUES DEEP LEARNING vs. NAÏVE BAYES vs. BACK PROPAGATION NEURAL NETWORKS IN WEB DOCUMENT EXTRACTION

    Directory of Open Access Journals (Sweden)

    J. Sharmila

    2016-01-01

    Full Text Available Web mining related exploration is getting the chance to be more essential these days in view of the reason that a lot of information is overseen through the web. Web utilization is expanding in an uncontrolled way. A particular framework is required for controlling such extensive measure of information in the web space. Web mining is ordered into three noteworthy divisions: Web content mining, web usage mining and web structure mining. Tak-Lam Wong has proposed a web content mining methodology in the exploration with the aid of Bayesian Networks (BN. In their methodology, they were learning on separating the web data and characteristic revelation in view of the Bayesian approach. Roused from their investigation, we mean to propose a web content mining methodology, in view of a Deep Learning Algorithm. The Deep Learning Algorithm gives the interest over BN on the basis that BN is not considered in any learning architecture planning like to propose system. The main objective of this investigation is web document extraction utilizing different grouping algorithm and investigation. This work extricates the data from the web URL. This work shows three classification algorithms, Deep Learning Algorithm, Bayesian Algorithm and BPNN Algorithm. Deep Learning is a capable arrangement of strategies for learning in neural system which is connected like computer vision, speech recognition, and natural language processing and biometrics framework. Deep Learning is one of the simple classification technique and which is utilized for subset of extensive field furthermore Deep Learning has less time for classification. Naive Bayes classifiers are a group of basic probabilistic classifiers in view of applying Bayes hypothesis with concrete independence assumptions between the features. At that point the BPNN algorithm is utilized for classification. Initially training and testing dataset contains more URL. We extract the content presently from the dataset. The

  16. [Biomedical engineering today : An overview from the viewpoint of the German Biomedical Engineering Society].

    Science.gov (United States)

    Schlötelburg, C; Becks, T; Stieglitz, T

    2010-08-01

    Biomedical engineering is characterized by the interdisciplinary co-operation of technology, science, and ways of thinking, probably more than any other technological area. The close interaction of engineering and information sciences with medicine and biology results in innovative products and methods, but also requires high standards for the interdisciplinary transfer of ideas into products for patients' benefits. This article describes the situation of biomedical engineering in Germany. It displays characteristics of the medical device industry and ranks it with respect to the international market. The research landscape is described as well as up-to-date research topics and trends. The national funding situation of research in biomedical engineering is reviewed and existing innovation barriers are discussed.

  17. Network and Ensemble Enabled Entity Extraction in Informal Text (NEEEEIT) final report.

    Energy Technology Data Exchange (ETDEWEB)

    Kegelmeyer, W. Philip,; Shead, Timothy M. [Sandia National Laboratories, Albuquerque, NM; Dunlavy, Daniel M. [Sandia National Laboratories, Albuquerque, NM

    2013-09-01

    This SAND report summarizes the activities and outcomes of the Network and Ensemble Enabled Entity Extraction in Informal Text (NEEEEIT) LDRD project, which addressed improving the accuracy of conditional random fields for named entity recognition through the use of ensemble methods. Conditional random fields (CRFs) are powerful, flexible probabilistic graphical models often used in supervised machine learning prediction tasks associated with sequence data. Specifically, they are currently the best known option for named entity recognition (NER) in text. NER is the process of labeling words in sentences with semantic identifiers such as %E2%80%9Cperson%E2%80%9D, %E2%80%9Cdate%E2%80%9D, or %E2%80%9Corganization%E2%80%9D. Ensembles are a powerful statistical inference meta-method that can make most supervised machine learning methods more accurate, faster, or both. Ensemble methods are normally best suited to %E2%80%9Cunstable%E2%80%9D classification methods with high variance error. CRFs applied to NER are very stable classifiers, and as such, would initially seem to be resistant to the benefits of ensembles. The NEEEEIT project nonetheless worked out how to generalize ensemble methods to CRFs, demonstrated that accuracy can indeed be improved by proper use of ensemble techniques, and generated a new CRF code, %E2%80%9CpyCrust%E2%80%9D and a surrounding application environment, %E2%80%9CNEEEEIT%E2%80%9D, which implement those improvements. The summary practical advice that results from this work, then, is: When making use of CRFs for label prediction tasks in machine learning, use the pyCrust CRF base classifier with NEEEEIT's bagging ensemble implementation. (If those codes are not available, then de-stablize your CRF code via every means available, and generate the bagged training sets by hand.) If you have ample pre-processing computational time, do %E2%80%9Cforward feature selection%E2%80%9D to find and remove counter-productive feature classes. Conversely

  18. Biomedical Device Technology Principles and Design

    CERN Document Server

    Chan, Anthony Y K

    2008-01-01

    For many years, the tools available to physicians were limited to a few simple handpieces such as stethoscopes, thermometers and syringes; medical professionals primarily relied on their senses and skills to perform diagnosis and disease mitigation. Today, diagnosis of medical problems is heavily dependent on the analysis of information made available by sophisticated medical machineries such as electrocardiographs, ultrasound scanners and laboratory analyzers. Patient treatments often involve specialized equipment such as cardiac pacemakers and electrosurgical units. Such biomedical instrumen

  19. BioLemmatizer: a lemmatization tool for morphological processing of biomedical text

    Directory of Open Access Journals (Sweden)

    Liu Haibin

    2012-04-01

    Full Text Available Abstract Background The wide variety of morphological variants of domain-specific technical terms contributes to the complexity of performing natural language processing of the scientific literature related to molecular biology. For morphological analysis of these texts, lemmatization has been actively applied in the recent biomedical research. Results In this work, we developed a domain-specific lemmatization tool, BioLemmatizer, for the morphological analysis of biomedical literature. The tool focuses on the inflectional morphology of English and is based on the general English lemmatization tool MorphAdorner. The BioLemmatizer is further tailored to the biological domain through incorporation of several published lexical resources. It retrieves lemmas based on the use of a word lexicon, and defines a set of rules that transform a word to a lemma if it is not encountered in the lexicon. An innovative aspect of the BioLemmatizer is the use of a hierarchical strategy for searching the lexicon, which enables the discovery of the correct lemma even if the input Part-of-Speech information is inaccurate. The BioLemmatizer achieves an accuracy of 97.5% in lemmatizing an evaluation set prepared from the CRAFT corpus, a collection of full-text biomedical articles, and an accuracy of 97.6% on the LLL05 corpus. The contribution of the BioLemmatizer to accuracy improvement of a practical information extraction task is further demonstrated when it is used as a component in a biomedical text mining system. Conclusions The BioLemmatizer outperforms other tools when compared with eight existing lemmatizers. The BioLemmatizer is released as an open source software and can be downloaded from http://biolemmatizer.sourceforge.net.

  20. Event extraction for DNA methylation

    Directory of Open Access Journals (Sweden)

    Ohta Tomoko

    2011-10-01

    Full Text Available Abstract Background We consider the task of automatically extracting DNA methylation events from the biomedical domain literature. DNA methylation is a key mechanism of epigenetic control of gene expression and implicated in many cancers, but there has been little study of automatic information extraction for DNA methylation. Results We present an annotation scheme for DNA methylation following the representation of the BioNLP shared task on event extraction, select a set of 200 abstracts including a representative sample of all PubMed citations relevant to DNA methylation, and introduce manual annotation for this corpus marking nearly 3000 gene/protein mentions and 1500 DNA methylation and demethylation events. We retrain a state-of-the-art event extraction system on the corpus and find that automatic extraction of DNA methylation events, the methylated genes, and their methylation sites can be performed at 78% precision and 76% recall. Conclusions Our results demonstrate that reliable extraction methods for DNA methylation events can be created through corpus annotation and straightforward retraining of a general event extraction system. The introduced resources are freely available for use in research from the GENIA project homepage http://www-tsujii.is.s.u-tokyo.ac.jp/GENIA.

  1. Biomedical applications of nisin.

    Science.gov (United States)

    Shin, J M; Gwak, J W; Kamarajan, P; Fenno, J C; Rickard, A H; Kapila, Y L

    2016-06-01

    Nisin is a bacteriocin produced by a group of Gram-positive bacteria that belongs to Lactococcus and Streptococcus species. Nisin is classified as a Type A (I) lantibiotic that is synthesized from mRNA and the translated peptide contains several unusual amino acids due to post-translational modifications. Over the past few decades, nisin has been used widely as a food biopreservative. Since then, many natural and genetically modified variants of nisin have been identified and studied for their unique antimicrobial properties. Nisin is FDA approved and generally regarded as a safe peptide with recognized potential for clinical use. Over the past two decades the application of nisin has been extended to biomedical fields. Studies have reported that nisin can prevent the growth of drug-resistant bacterial strains, such as methicillin-resistant Staphylococcus aureus, Streptococcus pneumoniae, Enterococci and Clostridium difficile. Nisin has now been shown to have antimicrobial activity against both Gram-positive and Gram-negative disease-associated pathogens. Nisin has been reported to have anti-biofilm properties and can work synergistically in combination with conventional therapeutic drugs. In addition, like host-defence peptides, nisin may activate the adaptive immune response and have an immunomodulatory role. Increasing evidence indicates that nisin can influence the growth of tumours and exhibit selective cytotoxicity towards cancer cells. Collectively, the application of nisin has advanced beyond its role as a food biopreservative. Thus, this review will describe and compare studies on nisin and provide insight into its future biomedical applications.

  2. Inexperienced clinicians can extract pathoanatomic information from MRI narrative reports with high reproducability for use in research/quality assurance

    DEFF Research Database (Denmark)

    Kent, Peter; Briggs, Andrew M; Albert, Hanne Birgit;

    2011-01-01

    Background Although reproducibility in reading MRI images amongst radiologists and clinicians has been studied previously, no studies have examined the reproducibility of inexperienced clinicians in extracting pathoanatomic information from magnetic resonance imaging (MRI) narrative reports...... pathoanatomic information from radiologist-generated MRI narrative reports. Methods Twenty MRI narrative reports were randomly extracted from an institutional database. A group of three physiotherapy students independently reviewed the reports and coded the presence of 14 common pathoanatomic findings using...... a categorical electronic coding matrix. Decision rules were developed after initial coding in an effort to resolve ambiguities in narrative reports. This process was repeated a further three times using separate samples of 20 MRI reports until no further ambiguities were identified (total n=80). Reproducibility...

  3. 大数据时代医学生物信息的挖掘和利用%Mining and Utilization of Bio-medical Information in the Time of Big Data

    Institute of Scientific and Technical Information of China (English)

    时钢; 王兴梅; 黄志民; 洪松林; 闫妍; 高伟伟; 门天男

    2014-01-01

    With the development of the hospital information construction,the progress of medical diagnostics and the use of high-throughput experimental equipment, medical data presentation of geometric growth showed the characteristic of big data.In medical research,the specimens library construction, clinical medical treatment, medical and health regulatory aspects put forward a huge chal enge,how to utilize existing medical information system and medical iological information construction in the future,has brought unprecedented opportunities for biomedical research too.To begin the work of big data research which is very meaningful to the construction of hospital informatization construction and biological specimen information database.The application of this research technique wil become the trend of the development of the biomedical science and technology, wil be the future of core technology in the field of bioinformatics research.So do the requirement of technical knowledge, infrastructure, personnel training content is very necessary.Big data wil infiltrate into the medical field, changing the medical research and practice of clinical medicine, medical management.%随着医院信息化的建设,医疗诊断手段进步和高通量实验设备的利用,医学数据呈现几何级数的增长表现出大数据的特征。如何利用现在已有的医疗信息系统和在将来医学生物信息化建设的问题上,对医学研究、标本库建设、临床医疗、医疗卫生监管等都提出了巨大的挑战,也为生物医学研究带来了前所未有的机遇。开展"大数据"相关研究工作对医院信息化建设、生物标本信息库建设是有着意义的。这种研究技术的应用必将成为生物医药科学技术发展的趋势,也必将是未来生物信息研究领域的核心技术。所以做好相关的技术知识了解、基础建设要求、人才培养内容是非常必要的。大数据必将渗透到医学领域,改变

  4. Extracting Information from the Atom-Laser Wave Function UsingInterferometric Measurement with a Laser Standing-Wave Grating

    Institute of Scientific and Technical Information of China (English)

    刘正东; 武强; 曾亮; 林宇; 朱诗尧

    2001-01-01

    The reconstruction of the atom-laser wave function is performed using an interferometric measurement with a standing-wave grating, and the results of this scheme are studied. The relations between the measurement data and the atomic wave function are also presented. This scheme is quite applicable and effectively avoids the initial random phase problem of the method that employs the laser running wave. The information which is encoded in the atom-laser wave is extracted.

  5. Multiscale computer modeling in biomechanics and biomedical engineering

    CERN Document Server

    2013-01-01

    This book reviews the state-of-the-art in multiscale computer modeling, in terms of both accomplishments and challenges. The information in the book is particularly useful for biomedical engineers, medical physicists and researchers in systems biology, mathematical biology, micro-biomechanics and biomaterials who are interested in how to bridge between traditional biomedical engineering work at the organ and tissue scales, and the newer arenas of cellular and molecular bioengineering.

  6. [The Chilean Association of Biomedical Journal Editors].

    Science.gov (United States)

    Reyes, H

    2001-01-01

    On September 29th, 2000, The Chilean Association of Biomedical Journal Editors was founded, sponsored by the "Comisión Nacional de Investigación Científica y Tecnológica (CONICYT)" (the Governmental Agency promoting and funding scientific research and technological development in Chile) and the "Sociedad Médica de Santiago" (Chilean Society of Internal Medicine). The Association adopted the goals of the World Association of Medical Editors (WAME) and therefore it will foster "cooperation and communication among Editors of Chilean biomedical journals; to improve editorial standards, to promote professionalism in medical editing through education, self-criticism and self-regulation; and to encourage research on the principles and practice of medical editing". Twenty nine journals covering a closely similar number of different biomedical sciences, medical specialties, veterinary, dentistry and nursing, became Founding Members of the Association. A Governing Board was elected: President: Humberto Reyes, M.D. (Editor, Revista Médica de Chile); Vice-President: Mariano del Sol, M.D. (Editor, Revista Chilena de Anatomía); Secretary: Anna María Prat (CONICYT); Councilors: Manuel Krauskopff, Ph.D. (Editor, Biological Research) and Maritza Rahal, M.D. (Editor, Revista de Otorrinolaringología y Cirugía de Cabeza y Cuello). The Association will organize a Symposium on Biomedical Journal Editing and will spread information stimulating Chilean biomedical journals to become indexed in international databases and in SciELO-Chile, the main Chilean scientific website (www.scielo.cl).

  7. Professional Identification for Biomedical Engineers

    Science.gov (United States)

    Long, Francis M.

    1973-01-01

    Discusses four methods of professional identification in biomedical engineering including registration, certification, accreditation, and possible membership qualification of the societies. Indicates that the destiny of the biomedical engineer may be under the control of a new profession, neither the medical nor the engineering. (CC)

  8. A New Paradigm for the Extraction of Information:Application to Enhancement of Visual Information in a Medical Application

    Institute of Scientific and Technical Information of China (English)

    V. Courboulay; A. Histace; M. Ménard; C.Cavaro-Menard

    2004-01-01

    The noninvasive evaluation of the cardiac function presents a great interest for the diagnosis of cardiovascular diseases. Tagged cardiac MRI allows the measurement of anatomical and functional myocardial parameters. This protocol generates a dark grid which is deformed with the myocardium displacement on both Short-Axis (SA) and Long-Axis (LA) frames in a time sequence. Visual evaluation of the grid deformation allows the estimation of the displacement inside the myocardium. The work described in this paper aims to make robust and reliable the visual enhancement of the grid tags on cardiac MRI sequences, thanks to an informational formalism based on Extreme Physical Informational (EPI). This approach leads to the development of an original diffusion pre-processing allowing us to make better the robustness of the visual detection and the following of the grid of tags.

  9. A Semantics and Data-Driven Biomedical Multimedia Software System

    Directory of Open Access Journals (Sweden)

    Shih-Hsi Liu

    2010-08-01

    Full Text Available Developing a large-scale biomedical multimedia software system is always a challenging task: Satisfaction of sundry and stringent biomedical multimedia related requirements and standards; Heterogeneous software deployment and communication environments; and tangling correlation between data/contents and software functionalities, among others. This paper introduces a novel biomedical multimedia software system developed under Service-Oriented Architecture (SOA. Such a system takes the advantage of interoperability of SOA to solve the heterogeneity and correlation problems. The paper also classifies the system into services, annotation, ontologies, semantics matching, and QoS optimization aspects which may potentially solve the requirements problem: By establishing data ontology with respect to data properties, contents, QoS, and biomedical regulations and expanding service ontology to describe more functional and QoS specifications supported by services, appropriate services for processing biomedical multimedia data may be discovered, performed, tuned up or replaced as needed. Lastly, a biomedical education project that improves the performance of feature extraction and classification processed afterwards is introduced to illustrate the advantages of our software system developed under SOA.

  10. Comparison of Qinzhou bay wetland landscape information extraction by three methods

    Directory of Open Access Journals (Sweden)

    X. Chang

    2014-04-01

    and OO is 219 km2, 193.70 km2, 217.40 km2 respectively. The result indicates that SC is in the f irst place, followed by OO approach, and the third DT method when used to extract Qingzhou Bay coastal wetland.

  11. Road Extraction and Network Building from Synthetic Aperture Radar Images using A-Priori Information

    NARCIS (Netherlands)

    Dekker, R.J.

    2008-01-01

    This paper describes a method for the extraction of road networks from radar images. Three phases can be distinguished: (1) detection of road lines, (2) network building, and (3) network fusion. The method has been demonstrated on two radar images, one urban and one rural. Despite the differences, t

  12. Checklists in biomedical publications

    Directory of Open Access Journals (Sweden)

    Pardal-Refoyo JL

    2013-12-01

    Full Text Available Introduction and objectives: the authors, reviewers, editors and readers must have specific tools that help them in the process of drafting, review, or reading the articles. Objective: to offer a summary of the major checklists for different types of biomedical research articles. Material and method: review literature and resources of the EQUATOR Network and adaptations in Spanish published by Medicina Clínica and Evidencias en Pediatría journals. Results: are the checklists elaborated by various working groups. (CONSORT and TREND, experimental studies for observational studies (STROBE, accuracy (STARD diagnostic studies, systematic reviews and meta-analyses (PRISMA and for studies to improve the quality (SQUIRE. Conclusions: the use of checklists help to improve the quality of articles and help to authors, reviewers, to the editor and readers in the development and understanding of the content.

  13. MEMS biomedical implants

    Institute of Scientific and Technical Information of China (English)

    Tai Yuchong

    2012-01-01

    The field of micro-electro-mechanical systems (MEMS) has advanced tremendously for the last 20 years. Most commercially noticeably, the field has successfully advanced from pressure sensors to micro physical sensors, such as accelerometers and gyros, for handheld electronics application. In parallel, MEMS has also advanced into micro total analysis system(TAS) and/or lab-on-a-chip applications. This article would discuss a relatively new but promising future direction towards MEMS biomedical implants. Specifically, Parylene C has been explored to be used as a good MEMS implant material and will be discussed in detail. Demonstrated implant devices, such as retinal and spinal cord implants, are presented in this article.

  14. A defocus-information-free autostereoscopic three-dimensional (3D) digital reconstruction method using direct extraction of disparity information (DEDI)

    Science.gov (United States)

    Li, Da; Cheung, Chifai; Zhao, Xing; Ren, Mingjun; Zhang, Juan; Zhou, Liqiu

    2016-10-01

    Autostereoscopy based three-dimensional (3D) digital reconstruction has been widely applied in the field of medical science, entertainment, design, industrial manufacture, precision measurement and many other areas. The 3D digital model of the target can be reconstructed based on the series of two-dimensional (2D) information acquired by the autostereoscopic system, which consists multiple lens and can provide information of the target from multiple angles. This paper presents a generalized and precise autostereoscopic three-dimensional (3D) digital reconstruction method based on Direct Extraction of Disparity Information (DEDI) which can be used to any transform autostereoscopic systems and provides accurate 3D reconstruction results through error elimination process based on statistical analysis. The feasibility of DEDI method has been successfully verified through a series of optical 3D digital reconstruction experiments on different autostereoscopic systems which is highly efficient to perform the direct full 3D digital model construction based on tomography-like operation upon every depth plane with the exclusion of the defocused information. With the absolute focused information processed by DEDI method, the 3D digital model of the target can be directly and precisely formed along the axial direction with the depth information.

  15. Review of spectral imaging technology in biomedical engineering: achievements and challenges.

    Science.gov (United States)

    Li, Qingli; He, Xiaofu; Wang, Yiting; Liu, Hongying; Xu, Dongrong; Guo, Fangmin

    2013-10-01

    Spectral imaging is a technology that integrates conventional imaging and spectroscopy to get both spatial and spectral information from an object. Although this technology was originally developed for remote sensing, it has been extended to the biomedical engineering field as a powerful analytical tool for biological and biomedical research. This review introduces the basics of spectral imaging, imaging methods, current equipment, and recent advances in biomedical applications. The performance and analytical capabilities of spectral imaging systems for biological and biomedical imaging are discussed. In particular, the current achievements and limitations of this technology in biomedical engineering are presented. The benefits and development trends of biomedical spectral imaging are highlighted to provide the reader with an insight into the current technological advances and its potential for biomedical research.

  16. The interaction of domain knowledge and linguistic structure in natural language processing: interpreting hypernymic propositions in biomedical text.

    Science.gov (United States)

    Rindflesch, Thomas C; Fiszman, Marcelo

    2003-12-01

    Interpretation of semantic propositions in free-text documents such as MEDLINE citations would provide valuable support for biomedical applications, and several approaches to semantic interpretation are being pursued in the biomedical informatics community. In this paper, we describe a methodology for interpreting linguistic structures that encode hypernymic propositions, in which a more specific concept is in a taxonomic relationship with a more general concept. In order to effectively process these constructions, we exploit underspecified syntactic analysis and structured domain knowledge from the Unified Medical Language System (UMLS). After introducing the syntactic processing on which our system depends, we focus on the UMLS knowledge that supports interpretation of hypernymic propositions. We first use semantic groups from the Semantic Network to ensure that the two concepts involved are compatible; hierarchical information in the Metathesaurus then determines which concept is more general and which more specific. A preliminary evaluation of a sample based on the semantic group Chemicals and Drugs provides 83% precision. An error analysis was conducted and potential solutions to the problems encountered are presented. The research discussed here serves as a paradigm for investigating the interaction between domain knowledge and linguistic structure in natural language processing, and could also make a contribution to research on automatic processing of discourse structure. Additional implications of the system we present include its integration in advanced semantic interpretation processors for biomedical text and its use for information extraction in specific domains. The approach has the potential to support a range of applications, including information retrieval and ontology engineering.

  17. Study on extraction of crop information using time-series MODIS data in the Chao Phraya Basin of Thailand

    Science.gov (United States)

    Tingting, Lv; Chuang, Liu

    2010-03-01

    In order to acquire the crop-related information in Chao Phraya Basin, time-series MODIS data were used in this paper. Although the spatial resolution of MODIS data is not very high, it is still useful for detecting very large-scale phenomenon, such as changes in seasonal vegetation patterns. After the data processing a general crop-related LULC (land use and land cover) map, cropping intensity map and cropping patterns map were produced. Analysis of these maps showed that the main land use type in the study area was farmland, most of which was dominated by rice. Rice fields mostly concentrated in the flood plains and double or triple rice-cropping system was commonly employed in this area. Maize, cassava, sugarcane and other upland crops were mainly distributed in the high alluvial terraces. Because these area often have water shortage problem particularly in the dry season which can support only one crop in a year, the cropping intensity was very low. However, some upland areas can be cultivated twice a year with crops which have short growing seasons. The crop information extracted from MODIS data sets were assessed by CBERS data, statistic data and so on. It was shown that MODIS derived crop information coincided well with the statistic data at the provincial level. At the same time, crop information extracted by MODIS data sets and CBERS were compared with each other which also showed similar spatial patterns.

  18. Advanced image collection, information extraction, and change detection in support of NN-20 broad area search and analysis

    Energy Technology Data Exchange (ETDEWEB)

    Petrie, G.M.; Perry, E.M.; Kirkham, R.R.; Slator, D.E. [and others

    1997-09-01

    This report describes the work performed at the Pacific Northwest National Laboratory (PNNL) for the U.S. Department of Energy`s Office of Nonproliferation and National Security, Office of Research and Development (NN-20). The work supports the NN-20 Broad Area Search and Analysis, a program initiated by NN-20 to improve the detection and classification of undeclared weapons facilities. Ongoing PNNL research activities are described in three main components: image collection, information processing, and change analysis. The Multispectral Airborne Imaging System, which was developed to collect georeferenced imagery in the visible through infrared regions of the spectrum, and flown on a light aircraft platform, will supply current land use conditions. The image information extraction software (dynamic clustering and end-member extraction) uses imagery, like the multispectral data collected by the PNNL multispectral system, to efficiently generate landcover information. The advanced change detection uses a priori (benchmark) information, current landcover conditions, and user-supplied rules to rank suspect areas by probable risk of undeclared facilities or proliferation activities. These components, both separately and combined, provide important tools for improving the detection of undeclared facilities.

  19. Biomedical engineering frontier research and converging technologies

    CERN Document Server

    Jun, Ho-Wook; Shin, Jennifer; Lee, SangHoon

    2016-01-01

    This book provides readers with an integrative overview of the latest research and developments in the broad field of biomedical engineering. Each of the chapters offers a timely review written by leading biomedical engineers and aims at showing how the convergence of scientific and engineering fields with medicine has created a new basis for practically solving problems concerning human health, wellbeing and disease. While some of the latest frontiers of biomedicine, such as neuroscience and regenerative medicine, are becoming increasingly dependent on new ideas and tools from other disciplines, the paradigm shift caused by technological innovations in the fields of information science, nanotechnology, and robotics is opening new opportunities in healthcare, besides dramatically changing the ways we actually practice science. At the same time, a new generation of engineers, fluent in many different scientific “languages,” is creating entirely new fields of research that approach the “old” questions f...

  20. Syntactic dependency parsers for biomedical-NLP.

    Science.gov (United States)

    Cohen, Raphael; Elhadad, Michael

    2012-01-01

    Syntactic parsers have made a leap in accuracy and speed in recent years. The high order structural information provided by dependency parsers is useful for a variety of NLP applications. We present a biomedical model for the EasyFirst parser, a fast and accurate parser for creating Stanford Dependencies. We evaluate the models trained in the biomedical domains of EasyFirst and Clear-Parser in a number of task oriented metrics. Both parsers provide stat of the art speed and accuracy in the Genia of over 89%. We show that Clear-Parser excels at tasks relating to negation identification while EasyFirst excels at tasks relating to Named Entities and is more robust to changes in domain.

  1. Extracting Information about the Initial State from the Black Hole Radiation.

    Science.gov (United States)

    Lochan, Kinjalk; Padmanabhan, T

    2016-02-05

    The crux of the black hole information paradox is related to the fact that the complete information about the initial state of a quantum field in a collapsing spacetime is not available to future asymptotic observers, belying the expectations from a unitary quantum theory. We study the imprints of the initial quantum state contained in a specific class of distortions of the black hole radiation and identify the classes of in states that can be partially or fully reconstructed from the information contained within. Even for the general in state, we can uncover some specific information. These results suggest that a classical collapse scenario ignores this richness of information in the resulting spectrum and a consistent quantum treatment of the entire collapse process might allow us to retrieve much more information from the spectrum of the final radiation.

  2. Cluster-Based Query Expansion Using Language Modeling for Biomedical Literature Retrieval

    Science.gov (United States)

    Xu, Xuheng

    2011-01-01

    The tremendously huge volume of biomedical literature, scientists' specific information needs, long terms of multiples words, and fundamental problems of synonym and polysemy have been challenging issues facing the biomedical information retrieval community researchers. Search engines have significantly improved the efficiency and effectiveness of…

  3. Keyword Extraction from a Document using Word Co-occurrence Statistical Information

    Science.gov (United States)

    Matsuo, Yutaka; Ishizuka, Mitsuru

    We present a new keyword extraction algorithm that applies to a single document without using a large corpus. Frequent terms are extracted first, then a set of co-occurrence between each term and the frequent terms, i.e., occurrences in the same sentences, is generated. The distribution of co-occurrence shows the importance of a term in the document as follows. If the probability distribution of co-occurrence between term a and the frequent terms is biased to a particular subset of the frequent terms, then term a is likely to be a keyword. The degree of the biases of the distribution is measured by χ²-measure. We show our algorithm performs well for indexing technical papers.

  4. A robust pointer segmentation in biomedical images toward building a visual ontology for biomedical article retrieval

    Science.gov (United States)

    You, Daekeun; Simpson, Matthew; Antani, Sameer; Demner-Fushman, Dina; Thoma, George R.

    2013-01-01

    Pointers (arrows and symbols) are frequently used in biomedical images to highlight specific image regions of interest (ROIs) that are mentioned in figure captions and/or text discussion. Detection of pointers is the first step toward extracting relevant visual features from ROIs and combining them with textual descriptions for a multimodal (text and image) biomedical article retrieval system. Recently we developed a pointer recognition algorithm based on an edge-based pointer segmentation method, and subsequently reported improvements made on our initial approach involving the use of Active Shape Models (ASM) for pointer recognition and region growing-based method for pointer segmentation. These methods contributed to improving the recall of pointer recognition but not much to the precision. The method discussed in this article is our recent effort to improve the precision rate. Evaluation performed on two datasets and compared with other pointer segmentation methods show significantly improved precision and the highest F1 score.

  5. Rapid Training of Information Extraction with Local and Global Data Views

    Science.gov (United States)

    2012-05-01

    Proceedings of the COLING, 1996. [35] Ralph Grishman, David Westbrook and Adam Meyers. NYUs English ACE 2005 System Description. ACE 2005 Evaluation...Conference on Artificial Intelligence. 2000. 93 [61] David Nadeau and Satoshi Sekine. A Survey of Named Entity Recognition and Classification. In: Sekine...relation extraction. In Proc. of COLING. 2008. [64] John Ross Quinlan . Induction of decision trees. Machine Learning, 1(1), 81- 106. 1986. [65] Lev

  6. Analysis of a Probabilistic Model of Redundancy in Unsupervised Information Extraction

    Science.gov (United States)

    2010-08-25

    noise. Example A in Figure 4 has strong evidence for a functional relation. 66 out of 70 extractions for was born in ( Mozart , PLACE) have the same y...unambiguous. 19 A. was born in( Mozart , PLACE): Salzburg(66), Germany(3), Vienna(1) B. was born in(John Adams, PLACE): Braintree(12), Quincy(10), Worcester(8...C. lived in( Mozart , PLACE): Vienna(20), Prague(13), Salzburg(5) Figure 4: Functional relations such as example A have a different distribution of y

  7. Advancement of Women in the Biomedical Workforce: Insights for Success.

    Science.gov (United States)

    Barfield, Whitney L; Plank-Bazinet, Jennifer L; Austin Clayton, Janine

    2016-08-01

    Women continue to face unique barriers in the biomedical workforce that affect their advancement and retention in this field. The National Institutes of Health (NIH) formed the Working Group on Women in Biomedical Careers to address these issues. Through the efforts of the working group, the NIH funded 14 research grants to identify barriers or to develop and/or test interventions to support women in the biomedical workforce. The grantees that were funded through this endeavor later established the grassroots Research Partnership on Women in Biomedical Careers, and they continue to conduct research and disseminate information on the state of women in academic medicine. This Commentary explores the themes introduced in a collection of articles organized by the research partnership and published in this issue of Academic Medicine. The authors highlight the role that government plays in the advancement of women in academic medicine and highlight the findings put forward in this collection.

  8. Handbook on advanced design and manufacturing technologies for biomedical devices

    CERN Document Server

    2013-01-01

    The last decades have seen remarkable advances in computer-aided design, engineering and manufacturing technologies, multi-variable simulation tools, medical imaging, biomimetic design, rapid prototyping, micro and nanomanufacturing methods and information management resources, all of which provide new horizons for the Biomedical Engineering fields and the Medical Device Industry. Handbook on Advanced Design and Manufacturing Technologies for Biomedical Devices covers such topics in depth, with an applied perspective and providing several case studies that help to analyze and understand the key factors of the different stages linked to the development of a novel biomedical device, from the conceptual and design steps, to the prototyping and industrialization phases. Main research challenges and future potentials are also discussed, taking into account relevant social demands and a growing market already exceeding billions of dollars. In time, advanced biomedical devices will decisively change methods and resu...

  9. Terahertz Imaging for Biomedical Applications Pattern Recognition and Tomographic Reconstruction

    CERN Document Server

    Yin, Xiaoxia; Abbott, Derek

    2012-01-01

    Terahertz Imaging for Biomedical Applications: Pattern Recognition and Tomographic Reconstruction presents the necessary algorithms needed to assist screening, diagnosis, and treatment, and these algorithms will play a critical role in the accurate detection of abnormalities present in biomedical imaging. Terahertz biomedical imaging has become an area of interest due to its ability to simultaneously acquire both image and spectral information. Terahertz imaging systems are being commercialized with an increasing number of trials performed in a biomedical setting. Terahertz tomographic imaging and detection technology contributes to the ability to identify opaque objects with clear boundaries,and would be useful to both in vivo and ex vivo environments. This book also: Introduces terahertz radiation techniques and provides a number of topical examples of signal and image processing, as well as machine learning Presents the most recent developments in an emerging field, terahertz radiation Utilizes new methods...

  10. Extracting depth information of 3-dimensional structures from a single-view X-ray Fourier-transform hologram.

    Science.gov (United States)

    Geilhufe, J; Tieg, C; Pfau, B; Günther, C M; Guehrs, E; Schaffert, S; Eisebitt, S

    2014-10-20

    We demonstrate how information about the three-dimensional structure of an object can be extracted from a single Fourier-transform X-ray hologram. In contrast to lens-based 3D imaging approaches that provide depth information of a specimen utilizing several images from different angles or via adjusting the focus to different depths, our method capitalizes on the use of the holographically encoded phase and amplitude information of the object's wavefield. It enables single-shot measurements of 3D objects at coherent X-ray sources. As the ratio of longitudinal resolution over transverse resolution scales proportional to the diameter of the reference beam aperture over the X-ray wavelength, we expect the approach to be particularly useful in the extreme ultraviolet and soft-X-ray regime.

  11. Publication speed and advanced online publication: Are biomedical Indian journals slow?

    Directory of Open Access Journals (Sweden)

    Akash Shah

    2016-01-01

    Full Text Available Objective: The aim of this study was to identify the publication speed (peer review time and publication time of biomedical Indian journals and identify the journals having the facility of advance online publication (AOP. Materials and Methods: Biomedical Indian journals were identified from the Journal Citation Report of 2013. Thirty original articles published between January 2012 and June 2014 were systematically selected from each journal. Information about the date of submission, revision, and acceptance were extracted from the full text of the articles. Median peer review time (submission to acceptance and publication time (acceptance to AOP/electronic publication were calculated for each journal. Results: Of the 19 journals studied, 5 (26.3%, 15 (78.9%, and 6 (31.6% journals did not mention details about date of submission, date of revision, and date of acceptance, respectively. The individual median peer review time of the journals ranged from 87 to 377.5 days and the combined median peer review time (interquartile range was 143.5 days (105.5, 238. The individual median publication time ranged from 14 to 349 days. The publication time for journals with AOP was significantly lesser (29.5 [19.6, 50.6] vs. 146.5 [126.5, 202.5]; P = 0.02 compared to journals without AOP. Impact factor of the journal did not correlate with the publication speed. The facility of AOP was provided by 6 (31.6% journals. Conclusions: Overall, the peer review time and publication time of biomedical Indian journals included in our study seems to be fairly long. Less than one-third of biomedical Indian journals provide the facility of AOP.

  12. Extracting principles for information management adaptability during crisis response: A dynamic capability view

    NARCIS (Netherlands)

    Bharosa, N.; Janssen, M.F.W.H.A.

    2010-01-01

    During crises, relief agency commanders have to make decisions in a complex and uncertain environment, requiring them to continuously adapt to unforeseen environmental changes. In the process of adaptation, the commanders depend on information management systems for information. Yet there are still

  13. Automated Methods to Extract Patient New Information from Clinical Notes in Electronic Health Record Systems

    Science.gov (United States)

    Zhang, Rui

    2013-01-01

    The widespread adoption of Electronic Health Record (EHR) has resulted in rapid text proliferation within clinical care. Clinicians' use of copying and pasting functions in EHR systems further compounds this by creating a large amount of redundant clinical information in clinical documents. A mixture of redundant information (especially outdated…

  14. Biomedical education for clinical engineers.

    Science.gov (United States)

    Langevin, Francois; Donadey, Alain; Hadjes, Pierre; Blagosklonov, Oleg

    2007-01-01

    Biomedical equipment Master's degree is recognized by the French Ministry of Health, since its creation in 1975 under the denomination of "Specialization for Hospital Biomedical Engineers". Since the new national status of technical staff in the public service by decree of September 5th of 1991, it allows to access directly to the level of Chief Hospital Engineer (first category, second class, by ordinance of October 23rd, 1992). Biomedical Engineers jobs in French hospitals are selected after an examination organized by the recruiting hospital. Master's graduates are most often the best qualified.

  15. Bounds on the entropy generated when timing information is extracted from microscopic systems

    CERN Document Server

    Janzing, D; Janzing, Dominik; Beth, Thomas

    2003-01-01

    We consider Hamiltonian quantum systems with energy bandwidth \\Delta E and show that each measurement that determines the time up to an error \\Delta t generates at least the entropy (\\hbar/(\\Delta t \\Delta E))^2/2. Our result describes quantitatively to what extent all timing information is quantum information in systems with limited energy. It provides a lower bound on the dissipated energy when timing information of microscopic systems is converted to classical information. This is relevant for low power computation since it shows the amount of heat generated whenever a band limited signal controls a classical bit switch. Our result provides a general bound on the information-disturbance trade-off for von-Neumann measurements that distinguish states on the orbits of continuous unitary one-parameter groups with bounded spectrum. In contrast, information gain without disturbance is possible for some completely positive semi-groups. This shows that readout of timing information can be possible without entropy ...

  16. Extraction of structural and chemical information from high angle annular dark-field image by an improved peaks finding method.

    Science.gov (United States)

    Yin, Wenhao; Huang, Rong; Qi, Ruijuan; Duan, Chungang

    2016-09-01

    With the development of spherical aberration (Cs) corrected scanning transmission electron microscopy (STEM), high angle annular dark filed (HAADF) imaging technique has been widely applied in the microstructure characterization of various advanced materials with atomic resolution. However, current qualitative interpretation of the HAADF image is not enough to extract all the useful information. Here a modified peaks finding method was proposed to quantify the HAADF-STEM image to extract structural and chemical information. Firstly, an automatic segmentation technique including numerical filters and watershed algorithm was used to define the sub-areas for each atomic column. Then a 2D Gaussian fitting was carried out to determine the atomic column positions precisely, which provides the geometric information at the unit-cell scale. Furthermore, a self-adaptive integration based on the column position and the covariance of statistical Gaussian distribution were performed. The integrated intensities show very high sensitivity on the mean atomic number with improved signal-to-noise (S/N) ratio. Consequently, the polarization map and strain distributions were rebuilt from a HAADF-STEM image of the rhombohedral and tetragonal BiFeO3 interface and a MnO2 monolayer in LaAlO3 /SrMnO3 /SrTiO3 heterostructure was discerned from its neighbor TiO2 layers. Microsc. Res. Tech. 79:820-826, 2016. © 2016 Wiley Periodicals, Inc.

  17. Extracting multiscale pattern information of fMRI based functional brain connectivity with application on classification of autism spectrum disorders.

    Directory of Open Access Journals (Sweden)

    Hui Wang

    Full Text Available We employed a multi-scale clustering methodology known as "data cloud geometry" to extract functional connectivity patterns derived from functional magnetic resonance imaging (fMRI protocol. The method was applied to correlation matrices of 106 regions of interest (ROIs in 29 individuals with autism spectrum disorders (ASD, and 29 individuals with typical development (TD while they completed a cognitive control task. Connectivity clustering geometry was examined at both "fine" and "coarse" scales. At the coarse scale, the connectivity clustering geometry produced 10 valid clusters with a coherent relationship to neural anatomy. A supervised learning algorithm employed fine scale information about clustering motif configurations and prevalence, and coarse scale information about intra- and inter-regional connectivity; the algorithm correctly classified ASD and TD participants with sensitivity of 82.8% and specificity of 82.8%. Most of the predictive power of the logistic regression model resided at the level of the fine-scale clustering geometry, suggesting that cellular versus systems level disturbances are more prominent in individuals with ASD. This article provides validation for this multi-scale geometric approach to extracting brain functional connectivity pattern information and for its use in classification of ASD.

  18. Extracting multiscale pattern information of fMRI based functional brain connectivity with application on classification of autism spectrum disorders.

    Science.gov (United States)

    Wang, Hui; Chen, Chen; Fushing, Hsieh

    2012-01-01

    We employed a multi-scale clustering methodology known as "data cloud geometry" to extract functional connectivity patterns derived from functional magnetic resonance imaging (fMRI) protocol. The method was applied to correlation matrices of 106 regions of interest (ROIs) in 29 individuals with autism spectrum disorders (ASD), and 29 individuals with typical development (TD) while they completed a cognitive control task. Connectivity clustering geometry was examined at both "fine" and "coarse" scales. At the coarse scale, the connectivity clustering geometry produced 10 valid clusters with a coherent relationship to neural anatomy. A supervised learning algorithm employed fine scale information about clustering motif configurations and prevalence, and coarse scale information about intra- and inter-regional connectivity; the algorithm correctly classified ASD and TD participants with sensitivity of 82.8% and specificity of 82.8%. Most of the predictive power of the logistic regression model resided at the level of the fine-scale clustering geometry, suggesting that cellular versus systems level disturbances are more prominent in individuals with ASD. This article provides validation for this multi-scale geometric approach to extracting brain functional connectivity pattern information and for its use in classification of ASD.

  19. Functional network and its application to extract information from chaotic communication

    Institute of Scientific and Technical Information of China (English)

    李卫斌; 焦李成

    2004-01-01

    In chaotic communication system, the useful signal is hidden in chaotic signal, so the general method does not work well. Due to the random feature of chaotic signal, a functional network-based method is presented. In this method,the neural functions are selected from some complete function set for the functional network to reconstruct the chaotic signal, so the useful signal hidden in chaotic background is extracted. In addition, its learning algorithm is presented here and the example proves its good preformance.

  20. Recent advancements in information extraction methodology and hardware for earth resources survey systems

    Science.gov (United States)

    Erickson, J. D.; Thomson, F. J.

    1974-01-01

    The present work discusses some recent developments in preprocessing and extractive processing techniques and hardware and in user applications model development for earth resources survey systems. The Multivariate Interactive Digital Analysis System (MIDAS) is currently being developed, and is an attempt to solve the problem of real time multispectral data processing in an operational system. The main features and design philosophy of this system are described. Examples of wetlands mapping and land resource inventory are presented. A user model developed for predicting the yearly production of mallard ducks from remote sensing and ancillary data is described.

  1. Wavelet analysis of molecular dynamics: Efficient extraction of time-frequency information in ultrafast optical processes

    Energy Technology Data Exchange (ETDEWEB)

    Prior, Javier; Castro, Enrique [Departamento de Física Aplicada, Universidad Politécnica de Cartagena, Cartagena 30202 (Spain); Chin, Alex W. [Theory of Condensed Matter Group, University of Cambridge, J J Thomson Avenue, Cambridge CB3 0HE (United Kingdom); Almeida, Javier; Huelga, Susana F.; Plenio, Martin B. [Institut für Theoretische Physik, Albert-Einstein-Allee 11, Universität Ulm, D-89069 Ulm (Germany)

    2013-12-14

    New experimental techniques based on nonlinear ultrafast spectroscopies have been developed over the last few years, and have been demonstrated to provide powerful probes of quantum dynamics in different types of molecular aggregates, including both natural and artificial light harvesting complexes. Fourier transform-based spectroscopies have been particularly successful, yet “complete” spectral information normally necessitates the loss of all information on the temporal sequence of events in a signal. This information though is particularly important in transient or multi-stage processes, in which the spectral decomposition of the data evolves in time. By going through several examples of ultrafast quantum dynamics, we demonstrate that the use of wavelets provide an efficient and accurate way to simultaneously acquire both temporal and frequency information about a signal, and argue that this greatly aids the elucidation and interpretation of physical process responsible for non-stationary spectroscopic features, such as those encountered in coherent excitonic energy transport.

  2. Wavelet analysis of molecular dynamics: efficient extraction of time-frequency information in ultrafast optical processes.

    Science.gov (United States)

    Prior, Javier; Castro, Enrique; Chin, Alex W; Almeida, Javier; Huelga, Susana F; Plenio, Martin B

    2013-12-14

    New experimental techniques based on nonlinear ultrafast spectroscopies have been developed over the last few years, and have been demonstrated to provide powerful probes of quantum dynamics in different types of molecular aggregates, including both natural and artificial light harvesting complexes. Fourier transform-based spectroscopies have been particularly successful, yet "complete" spectral information normally necessitates the loss of all information on the temporal sequence of events in a signal. This information though is particularly important in transient or multi-stage processes, in which the spectral decomposition of the data evolves in time. By going through several examples of ultrafast quantum dynamics, we demonstrate that the use of wavelets provide an efficient and accurate way to simultaneously acquire both temporal and frequency information about a signal, and argue that this greatly aids the elucidation and interpretation of physical process responsible for non-stationary spectroscopic features, such as those encountered in coherent excitonic energy transport.

  3. Investigation of the Impact of Extracting and Exchanging Health Information by Using Internet and Social Networks

    Science.gov (United States)

    Pistolis, John; Zimeras, Stelios; Chardalias, Kostas; Roupa, Zoe; Fildisis, George; Diomidous, Marianna

    2016-01-01

    Introduction: Social networks (1) have been embedded in our daily life for a long time. They constitute a powerful tool used nowadays for both searching and exchanging information on different issues by using Internet searching engines (Google, Bing, etc.) and Social Networks (Facebook, Twitter etc.). In this paper, are presented the results of a research based on the frequency and the type of the usage of the Internet and the Social Networks by the general public and the health professionals. Objectives: The objectives of the research were focused on the investigation of the frequency of seeking and meticulously searching for health information in the social media by both individuals and health practitioners. The exchanging of information is a procedure that involves the issues of reliability and quality of information. Methods: In this research, by using advanced statistical techniques an effort is made to investigate the participant’s profile in using social networks for searching and exchanging information on health issues. Results: Based on the answers 93 % of the people, use the Internet to find information on health-subjects. Considering principal component analysis, the most important health subjects were nutrition (0.719 %), respiratory issues (0.79 %), cardiological issues (0.777%), psychological issues (0.667%) and total (73.8%). Conclusions: The research results, based on different statistical techniques revealed that the 61.2% of the males and 56.4% of the females intended to use the social networks for searching medical information. Based on the principal components analysis, the most important sources that the participants mentioned, were the use of the Internet and social networks for exchanging information on health issues. These sources proved to be of paramount importance to the participants of the study. The same holds for nursing, medical and administrative staff in hospitals. PMID:27482135

  4. Extracting protein dynamics information from overlapped NMR signals using relaxation dispersion difference NMR spectroscopy

    Energy Technology Data Exchange (ETDEWEB)

    Konuma, Tsuyoshi [Icahn School of Medicine at Mount Sinai, Department of Structural and Chemical Biology (United States); Harada, Erisa [Suntory Foundation for Life Sciences, Bioorganic Research Institute (Japan); Sugase, Kenji, E-mail: sugase@sunbor.or.jp, E-mail: sugase@moleng.kyoto-u.ac.jp [Kyoto University, Department of Molecular Engineering, Graduate School of Engineering (Japan)

    2015-12-15

    Protein dynamics plays important roles in many biological events, such as ligand binding and enzyme reactions. NMR is mostly used for investigating such protein dynamics in a site-specific manner. Recently, NMR has been actively applied to large proteins and intrinsically disordered proteins, which are attractive research targets. However, signal overlap, which is often observed for such proteins, hampers accurate analysis of NMR data. In this study, we have developed a new methodology called relaxation dispersion difference that can extract conformational exchange parameters from overlapped NMR signals measured using relaxation dispersion spectroscopy. In relaxation dispersion measurements, the signal intensities of fluctuating residues vary according to the Carr-Purcell-Meiboon-Gill pulsing interval, whereas those of non-fluctuating residues are constant. Therefore, subtraction of each relaxation dispersion spectrum from that with the highest signal intensities, measured at the shortest pulsing interval, leaves only the signals of the fluctuating residues. This is the principle of the relaxation dispersion difference method. This new method enabled us to extract exchange parameters from overlapped signals of heme oxygenase-1, which is a relatively large protein. The results indicate that the structural flexibility of a kink in the heme-binding site is important for efficient heme binding. Relaxation dispersion difference requires neither selectively labeled samples nor modification of pulse programs; thus it will have wide applications in protein dynamics analysis.

  5. Functionalized carbon nanotubes: biomedical applications.

    Science.gov (United States)

    Vardharajula, Sandhya; Ali, Sk Z; Tiwari, Pooja M; Eroğlu, Erdal; Vig, Komal; Dennis, Vida A; Singh, Shree R

    2012-01-01

    Carbon nanotubes (CNTs) are emerging as novel nanomaterials for various biomedical applications. CNTs can be used to deliver a variety of therapeutic agents, including biomolecules, to the target disease sites. In addition, their unparalleled optical and electrical properties make them excellent candidates for bioimaging and other biomedical applications. However, the high cytotoxicity of CNTs limits their use in humans and many biological systems. The biocompatibility and low cytotoxicity of CNTs are attributed to size, dose, duration, testing systems, and surface functionalization. The functionalization of CNTs improves their solubility and biocompatibility and alters their cellular interaction pathways, resulting in much-reduced cytotoxic effects. Functionalized CNTs are promising novel materials for a variety of biomedical applications. These potential applications are particularly enhanced by their ability to penetrate biological membranes with relatively low cytotoxicity. This review is directed towards the overview of CNTs and their functionalization for biomedical applications with minimal cytotoxicity.

  6. New Directions for Biomedical Engineering

    Science.gov (United States)

    Plonsey, Robert

    1973-01-01

    Discusses the definition of "biomedical engineering" and the development of educational programs in the field. Includes detailed descriptions of the roles of bioengineers, medical engineers, and chemical engineers. (CC)

  7. Molecular Biomedical Imaging Laboratory (MBIL)

    Data.gov (United States)

    Federal Laboratory Consortium — The Molecular Biomedical Imaging Laboratory (MBIL) is adjacent-a nd has access-to the Department of Radiology and Imaging Sciences clinical imaging facilities. MBIL...

  8. Biomedical engineer: an international job.

    Science.gov (United States)

    Crolet, Jean-Marie

    2007-01-01

    Biomedical engineer is an international job for several reasons and it means that the knowledge of at least one foreign language is a necessity. A geographical and structural analysis of the biomedical sector concludes to the teaching of a second foreign language. But in spite of the presence of adequate means, it is not possible for us for the moment to set up such a teaching. This paper presents the solution we have chosen in the framework of Erasmus exchanges.

  9. Hydroxyapatite coatings for biomedical applications

    CERN Document Server

    Zhang, Sam

    2013-01-01

    Hydroxyapatite coatings are of great importance in the biological and biomedical coatings fields, especially in the current era of nanotechnology and bioapplications. With a bonelike structure that promotes osseointegration, hydroxyapatite coating can be applied to otherwise bioinactive implants to make their surface bioactive, thus achieving faster healing and recovery. In addition to applications in orthopedic and dental implants, this coating can also be used in drug delivery. Hydroxyapatite Coatings for Biomedical Applications explores developments in the processing and property characteri

  10. John Glenn Biomedical Engineering Consortium

    Science.gov (United States)

    Nall, Marsha

    2004-01-01

    The John Glenn Biomedical Engineering Consortium is an inter-institutional research and technology development, beginning with ten projects in FY02 that are aimed at applying GRC expertise in fluid physics and sensor development with local biomedical expertise to mitigate the risks of space flight on the health, safety, and performance of astronauts. It is anticipated that several new technologies will be developed that are applicable to both medical needs in space and on earth.

  11. Cognitive and learning sciences in biomedical and health instructional design: A review with lessons for biomedical informatics education.

    Science.gov (United States)

    Patel, Vimla L; Yoskowitz, Nicole A; Arocha, Jose F; Shortliffe, Edward H

    2009-02-01

    Theoretical and methodological advances in the cognitive and learning sciences can greatly inform curriculum and instruction in biomedicine and also educational programs in biomedical informatics. It does so by addressing issues such as the processes related to comprehension of medical information, clinical problem-solving and decision-making, and the role of technology. This paper reviews these theories and methods from the cognitive and learning sciences and their role in addressing current and future needs in designing curricula, largely using illustrative examples drawn from medical education. The lessons of this past work are also applicable, however, to biomedical and health professional curricula in general, and to biomedical informatics training, in particular. We summarize empirical studies conducted over two decades on the role of memory, knowledge organization and reasoning as well as studies of problem-solving and decision-making in medical areas that inform curricular design. The results of this research contribute to the design of more informed curricula based on empirical findings about how people learn and think, and more specifically, how expertise is developed. Similarly, the study of practice can also help to shape theories of human performance, technology-based learning, and scientific and professional collaboration that extend beyond the domain of medicine. Just as biomedical science has revolutionized health care practice, research in the cognitive and learning sciences provides a scientific foundation for education in biomedicine, the health professions, and biomedical informatics.

  12. Biomedical Applications of NASA Science and Technology

    Science.gov (United States)

    Brown, James N., Jr.

    1968-01-01

    During the period 15 September 1968 to 14 December 1968, the NASA supported Biomedical Application Team at the Research Triangle Institute has identified 6 new problems, performed significant activities on 15 of the active problems identified previously, performed 5 computer searches of the NASA aerospace literature, and maintained one current awareness search. As a partial result of these activities, one technology transfer was accomplished. As a part of continuing problem review, 13 problems were classified inactive. Activities during the quarter involved all phases of team activity with respect to biomedical problems. As has been observed in preceding years, it has been exceedingly difficult to arrange meetings with medical investigators during the fourth quarter of the calendar year. This is a result of a combination of factors. Teaching requirements, submission of grant applications and holidays are the most significant factors involved. As a result, the numbers of new problems identified and of transfers and potential transfers are relatively low during this quarter. Most of our activities have thus been directed toward obtaining information related to problems already identified. Consequently, during the next quarter we will follow up on these activities with the expectation that transfers will be accomplished on a number of them. In addition, the normal availability of researchers to the team is expected to be restored during this quarter, permitting an increase in new problem identification activities as well as follow-up with other researchers on old problems. Another activity scheduled for the next quarter is consultation with several interested biomedical equipment manufacturers to explore means of effective interaction between the Biomedical Application Team and these companies.

  13. Extracting information about the initial state from the black hole radiation

    CERN Document Server

    Lochan, Kinjalk

    2015-01-01

    The crux of the black hole information paradox is related to the fact that the complete information about the initial state of a quantum field in a collapsing spacetime is not available to future asymptotic observers, belying the expectations from a unitary quantum theory. We study the imprints of the initial quantum state, contained in the distortions of the black hole radiation from the thermal spectrum, which can be detected by the asymptotic observers. We identify the class of in-states which can be fully reconstructed from the information contained in the distortions at the semiclassical level. Even for the general in-state, we can uncover a specific amount of information about the initial state. For a large class of initial states, some specific observables defined in the initial Hilbert space are completely determined from the resulting final spectrum. These results suggest that a \\textit{classical} collapse scenario ignores this richness of information in the resulting spectrum and a consistent quantu...

  14. A Novel Approach for Text Categorization of Unorganized data based with Information Extraction

    Directory of Open Access Journals (Sweden)

    Suneetha Manne,

    2011-07-01

    Full Text Available Internet has made a profound change in the lives of many enthusiastic innovators and researchers. The information available on the web has knocked the doors of Knowledge Discovery leading to a new Information era. Unfortunately, most Search Engines provide web content which is irrelevant to the information intended to the browser. Many Text Categorization techniques for web content have been developed, to recognize the given document’s category but failed to make trust worthy results. This paper primarily focuses on web content categorization based on classic summarization technique by enabling the classification at word level. The web document is preprocessed first which involves filtering the content with classical techniques and then is converted into organized data. The organized data is then treated with predefined hierarchical categorical set to identify theexact category.

  15. Adaptive extraction of emotion-related EEG segments using multidimensional directed information in time-frequency domain.

    Science.gov (United States)

    Petrantonakis, Panagiotis C; Hadjileontiadis, Leontios J

    2010-01-01

    Emotion discrimination from electroencephalogram (EEG) has gained attention the last decade as a user-friendly and effective approach to EEG-based emotion recognition (EEG-ER) systems. Nevertheless, challenging issues regarding the emotion elicitation procedure, especially its effectiveness, raise. In this work, a novel method, which not only evaluates the degree of emotion elicitation but localizes the emotion information in the time-frequency domain, as well, is proposed. The latter, incorporates multidimensional directed information at the time-frequency EEG representation, extracted using empirical mode decomposition, and introduces an asymmetry index for adaptive emotion-related EEG segment selection. Experimental results derived from 16 subjects visually stimulated with pictures from the valence/arousal space drawn from the International Affective Picture System database, justify the effectiveness of the proposed approach and its potential contribution to the enhancement of EEG-ER systems.

  16. Extracting DC bus current information for optimal phase correction and current ripple in sensorless brushless DC motor drive

    Institute of Scientific and Technical Information of China (English)

    Zu-sheng HO; Chii-maw UANG; Ping-chieh WANG

    2014-01-01

    Brushless DC motor (BLDCM) sensorless driving technology is becoming increasingly established. However, op-timal phase correction still relies on complex calculations or algorithms. In finding the correct commutation point, the problem of phase lag is introduced. In this paper, we extract DC bus current information for auto-calibrating the phase shift to obtain the correct commutation point and optimize the control of BLDC sensorless driving. As we capture only DC bus current information, the original shunt resistor is used in the BLDCM driver and there is no need to add further current sensor components. Software processing using only simple arithmetic operations successfully accomplishes the phase correction. Experimental results show that the proposed method can operate accurately and stably at low or high speed, with light or heavy load, and is suitable for practical applications. This approach will not increase cost but will achieve the best performance/cost ratio and meet market expectations.

  17. Amplitude extraction in pseudoscalar-meson photoproduction: towards a situation of complete information

    CERN Document Server

    Nys, Jannes; Ryckebusch, Jan

    2015-01-01

    A complete set for pseudoscalar-meson photoproduction is a minimum set of observables from which one can determine the underlying reaction amplitudes unambiguously. The complete sets considered in this work involve single- and double-polarization observables. It is argued that for extracting amplitudes from data, the transversity representation of the reaction amplitudes offers advantages over alternate representations. It is shown that with the available single-polarization data for the p({\\gamma},K^+)\\Lambda reaction, the energy and angular dependence of the moduli of the normalized transversity amplitudes in the resonance region can be determined to a fair accuracy. Determining the relative phases of the amplitudes from double-polarization observables is far less evident.

  18. Architecture and data processing alternatives for the TSE computer. Volume 2: Extraction of topological information from an image by the Tse computer

    Science.gov (United States)

    Jones, J. R.; Bodenheimer, R. E.

    1976-01-01

    A simple programmable Tse processor organization and arithmetic operations necessary for extraction of the desired topological information are described. Hardware additions to this organization are discussed along with trade-offs peculiar to the tse computing concept. An improved organization is presented along with the complementary software for the various arithmetic operations. The performance of the two organizations is compared in terms of speed, power, and cost. Software routines developed to extract the desired information from an image are included.

  19. Bio-SCoRes: A Smorgasbord Architecture for Coreference Resolution in Biomedical Text.

    Directory of Open Access Journals (Sweden)

    Halil Kilicoglu

    Full Text Available Coreference resolution is one of the fundamental and challenging tasks in natural language processing. Resolving coreference successfully can have a significant positive effect on downstream natural language processing tasks, such as information extraction and question answering. The importance of coreference resolution for biomedical text analysis applications has increasingly been acknowledged. One of the difficulties in coreference resolution stems from the fact that distinct types of coreference (e.g., anaphora, appositive are expressed with a variety of lexical and syntactic means (e.g., personal pronouns, definite noun phrases, and that resolution of each combination often requires a different approach. In the biomedical domain, it is common for coreference annotation and resolution efforts to focus on specific subcategories of coreference deemed important for the downstream task. In the current work, we aim to address some of these concerns regarding coreference resolution in biomedical text. We propose a general, modular framework underpinned by a smorgasbord architecture (Bio-SCoRes, which incorporates a variety of coreference types, their mentions and allows fine-grained specification of resolution strategies to resolve coreference of distinct coreference type-mention pairs. For development and evaluation, we used a corpus of structured drug labels annotated with fine-grained coreference information. In addition, we evaluated our approach on two other corpora (i2b2/VA discharge summaries and protein coreference dataset to investigate its generality and ease of adaptation to other biomedical text types. Our results demonstrate the usefulness of our novel smorgasbord architecture. The specific pipelines based on the architecture perform successfully in linking coreferential mention pairs, while we find that recognition of full mention clusters is more challenging. The corpus of structured drug labels (SPL as well as the components of Bio

  20. Bio-SCoRes: A Smorgasbord Architecture for Coreference Resolution in Biomedical Text.

    Science.gov (United States)

    Kilicoglu, Halil; Demner-Fushman, Dina

    2016-01-01

    Coreference resolution is one of the fundamental and challenging tasks in natural language processing. Resolving coreference successfully can have a significant positive effect on downstream natural language processing tasks, such as information extraction and question answering. The importance of coreference resolution for biomedical text analysis applications has increasingly been acknowledged. One of the difficulties in coreference resolution stems from the fact that distinct types of coreference (e.g., anaphora, appositive) are expressed with a variety of lexical and syntactic means (e.g., personal pronouns, definite noun phrases), and that resolution of each combination often requires a different approach. In the biomedical domain, it is common for coreference annotation and resolution efforts to focus on specific subcategories of coreference deemed important for the downstream task. In the current work, we aim to address some of these concerns regarding coreference resolution in biomedical text. We propose a general, modular framework underpinned by a smorgasbord architecture (Bio-SCoRes), which incorporates a variety of coreference types, their mentions and allows fine-grained specification of resolution strategies to resolve coreference of distinct coreference type-mention pairs. For development and evaluation, we used a corpus of structured drug labels annotated with fine-grained coreference information. In addition, we evaluated our approach on two other corpora (i2b2/VA discharge summaries and protein coreference dataset) to investigate its generality and ease of adaptation to other biomedical text types. Our results demonstrate the usefulness of our novel smorgasbord architecture. The specific pipelines based on the architecture perform successfully in linking coreferential mention pairs, while we find that recognition of full mention clusters is more challenging. The corpus of structured drug labels (SPL) as well as the components of Bio-SCoRes and

  1. Named entity extraction and disambiguation for informal text: the missing link

    NARCIS (Netherlands)

    Badieh Habib Morgan, Mena

    2014-01-01

    Social media content represents a large portion of all textual content appearing on the Internet. These streams of user generated content (UGC) provide an opportunity and challenge for media analysts to analyze huge amount of new data and use them to infer and reason with new information. An example

  2. The Exponentially Embedded Family of Distributions for Effective Data Representation, Information Extraction, and Decision Making

    Science.gov (United States)

    2013-03-01

    unlimited. This is equivalent to Gram-Schmidt orthogonalization for Gaussian PDFs (see Figure 2). Pt (true PDF) Pr(t; Ho) -~- · Prr (best...approximation) additional information of T2 Figure 2: Best Approximation For one sensor we construct and for two sensors we construct Prr = Pryi ,7]2

  3. An Approach for Comparative Research Between Ontology Building & Learning Tools for Information Extraction & Retrieval

    Directory of Open Access Journals (Sweden)

    Dr Suresh Jain C. S. Bhatia Dharmendra Gupta Sumit Jain Bharat Pahadiya

    2012-02-01

    Full Text Available Information available on the web is huge & it covers diversified fields. Nowadays most of search engines use essentially keyword based search techniques. We simply specify a set of keywords or query as a request and a reference we get a list of pages, ranked based on similarity of query. Currently searching web face with one problem that many times outcome is not satisfactory because of irrelevance of the information. Searching the exact information from such a huge repository of unstructured web data is still main area of research interest. One solution to achieve this is Semantic Web. Ontology is an effective concept commonly used for the Semantic Web. Ontology is “an explicit specification of a conceptualization”. There are two main pillars of semantic Web one is Problem Solving Methods & another is Ontology. Ontology building is a tedious job and a time consuming task for user. The quality of ontology plays an important role in information retrieval application .This paper deals with features & familiarity with different Ontology building & learning tools. After all the preliminary knowledge about all tools & software we have made research about specific features & services provided by some tools & identified the optimum tool in all respect for particularly for our further research project.

  4. Extracting additional risk managers information from a risk assessment of Listeria monocytogenes in deli meats

    NARCIS (Netherlands)

    Pérez-Rodríguez, F.; Asselt, van E.D.; García-Gimeno, R.M.; Zurera, G.; Zwietering, M.H.

    2007-01-01

    The risk assessment study of Listeria monocytogenes in ready-to-eat foods conducted by the U.S. Food and Drug Administration is an example of an extensive quantitative microbiological risk assessment that could be used by risk analysts and other scientists to obtain information and by managers and s

  5. The Promise of Information and Communication Technology in Healthcare: Extracting Value From the Chaos.

    Science.gov (United States)

    Mamlin, Burke W; Tierney, William M

    2016-01-01

    Healthcare is an information business with expanding use of information and communication technologies (ICTs). Current ICT tools are immature, but a brighter future looms. We examine 7 areas of ICT in healthcare: electronic health records (EHRs), health information exchange (HIE), patient portals, telemedicine, social media, mobile devices and wearable sensors and monitors, and privacy and security. In each of these areas, we examine the current status and future promise, highlighting how each might reach its promise. Steps to better EHRs include a universal programming interface, universal patient identifiers, improved documentation and improved data analysis. HIEs require federal subsidies for sustainability and support from EHR vendors, targeting seamless sharing of EHR data. Patient portals must bring patients into the EHR with better design and training, greater provider engagement and leveraging HIEs. Telemedicine needs sustainable payment models, clear rules of engagement, quality measures and monitoring. Social media needs consensus on rules of engagement for providers, better data mining tools and approaches to counter disinformation. Mobile and wearable devices benefit from a universal programming interface, improved infrastructure, more rigorous research and integration with EHRs and HIEs. Laws for privacy and security need updating to match current technologies, and data stewards should share information on breaches and standardize best practices. ICT tools are evolving quickly in healthcare and require a rational and well-funded national agenda for development, use and assessment.

  6. RPCs in biomedical applications

    Science.gov (United States)

    Belli, G.; De Vecchi, C.; Giroletti, E.; Guida, R.; Musitelli, G.; Nardò, R.; Necchi, M. M.; Pagano, D.; Ratti, S. P.; Sani, G.; Vicini, A.; Vitulo, P.; Viviani, C.

    2006-08-01

    We are studying possible applications of Resistive Plate Chambers (RPCs) in the biomedical domain such as Positron Emission Tomography (PET). The use of RPCs in PET can provide several improvements on the usual scintillation-based detectors. The most striking features are the extremely good spatial and time resolutions. They can be as low as 50 μm and 25 ps respectively, to be compared to the much higher intrinsic limits in bulk detectors. Much efforts have been made to investigate suitable materials to make RPCs sensitive to 511 keV photons. For this reason, we are studying different types of coating employing high Z materials with proper electrical resistivity. Later investigations explored the possibility of coating glass electrodes by mean of serigraphy techniques, employing oxide based mixtures with a high density of high Z materials; the efficiency is strongly dependent on its thickness and it reaches a maximum for a characteristic value that is a function of the compound (usually a few hundred microns). The most promising mixtures seem to be PbO, Bi 2O 3 and Tl 2O. Preliminary gamma efficiency measurements for a Multigap RPC prototype (MRPC) are presented as well as simulations using GEANT4-based framework. The MRPC has 5 gas gaps; their spacings are kept by 0.3 mm diameter nylon fishing line, electrodes are made of thin glasses (1 mm for the outer electrodes, 0.15-0.4 mm for the inner ones). The detector is enclosed in a metallic gas-tight box, filled with a C 2H 2F 4 92.5%, SF 6 2.5%, C 4H 10 5% mixture. Different gas mixtures are being studied increasing the SF6 percentage and results of efficiency as a function of the new mixtures will be presented.

  7. RPCs in biomedical applications

    Energy Technology Data Exchange (ETDEWEB)

    Belli, G. [Dipartimento di Fisica Nucleare e Teorica and Sezione INFN, via A. Bassi 6, 27100 Pavia (Italy); De Vecchi, C. [Dipartimento di Fisica Nucleare e Teorica and Sezione INFN, via A. Bassi 6, 27100 Pavia (Italy); Giroletti, E. [Dipartimento di Fisica Nucleare e Teorica and Sezione INFN, via A. Bassi 6, 27100 Pavia (Italy); Guida, R. [Dipartimento di Fisica Nucleare e Teorica and Sezione INFN, via A. Bassi 6, 27100 Pavia (Italy); Musitelli, G. [Dipartimento di Fisica Nucleare e Teorica and Sezione INFN, via A. Bassi 6, 27100 Pavia (Italy); Nardo, R. [Dipartimento di Fisica Nucleare e Teorica and Sezione INFN, via A. Bassi 6, 27100 Pavia (Italy); Necchi, M.M. [Dipartimento di Fisica Nucleare e Teorica and Sezione INFN, via A. Bassi 6, 27100 Pavia (Italy); Pagano, D. [Dipartimento di Fisica Nucleare e Teorica and Sezione INFN, via A. Bassi 6, 27100 Pavia (Italy); Ratti, S.P. [Dipartimento di Fisica Nucleare e Teorica and Sezione INFN, via A. Bassi 6, 27100 Pavia (Italy); Sani, G. [Dipartimento di Fisica Nucleare e Teorica and Sezione INFN, via A. Bassi 6, 27100 Pavia (Italy); Vicini, A. [Dipartimento di Fisica Nucleare e Teorica and Sezione INFN, via A. Bassi 6, 27100 Pavia (Italy); Vitulo, P. [Dipartimento di Fisica Nucleare e Teorica and Sezione INFN, via A. Bassi 6, 27100 Pavia (Italy); Viviani, C. [Dipartimento di Fisica Nucleare e Teorica and Sezione INFN, via A. Bassi 6, 27100 Pavia (Italy)

    2006-08-15

    We are studying possible applications of Resistive Plate Chambers (RPCs) in the biomedical domain such as Positron Emission Tomography (PET). The use of RPCs in PET can provide several improvements on the usual scintillation-based detectors. The most striking features are the extremely good spatial and time resolutions. They can be as low as 50 {mu}m and 25 ps respectively, to be compared to the much higher intrinsic limits in bulk detectors. Much efforts have been made to investigate suitable materials to make RPCs sensitive to 511 keV photons. For this reason, we are studying different types of coating employing high Z materials with proper electrical resistivity. Later investigations explored the possibility of coating glass electrodes by mean of serigraphy techniques, employing oxide based mixtures with a high density of high Z materials; the efficiency is strongly dependent on its thickness and it reaches a maximum for a characteristic value that is a function of the compound (usually a few hundred microns). The most promising mixtures seem to be PbO, Bi{sub 2}O{sub 3} and Tl{sub 2}O. Preliminary gamma efficiency measurements for a Multigap RPC prototype (MRPC) are presented as well as simulations using GEANT4-based framework. The MRPC has 5 gas gaps; their spacings are kept by 0.3 mm diameter nylon fishing line, electrodes are made of thin glasses (1 mm for the outer electrodes, 0.15-0.4 mm for the inner ones). The detector is enclosed in a metallic gas-tight box, filled with a C{sub 2}H{sub 2}F{sub 4} 92.5%, SF{sub 6} 2.5%, C{sub 4}H{sub 10} 5% mixture. Different gas mixtures are being studied increasing the SF6 percentage and results of efficiency as a function of the new mixtures will be presented.

  8. Extracting Feature Information and its Visualization Based on the Characteristic Defect Octave Frequencies in a Rolling Element Bearing

    Directory of Open Access Journals (Sweden)

    Jianyu Lei

    2007-10-01

    Full Text Available Monitoring the condition of rolling element bearings and defect diagnosis has received considerable attention for many years because the majority of problems in rotating machines are caused by defective bearings. In order to monitor conditions and diagnose defects in a rolling element bearing, a new approach is developed, based on the characteristic defect octave frequencies. The characteristic defect frequencies make it possible to detect the presence of a defect and diagnose in what part of the bearing the defect appears. However, because the characteristic defect frequencies vary with rotational speed, it is difficult to extract feature information from data at variable rotational speeds. In this paper, the characteristic defect octave frequencies, which do not vary with rotation speed, are introduced to replace the characteristic defect frequencies. Therefore feature information can be easily extracted. Moreover, based on characteristic defect octave frequencies, an envelope spectrum array, which associates 3-D visualization technology with extremum envelope spectrum technology, is established. This method has great advantages in acquiring the characteristics and trends of the data and achieves a straightforward and creditable result.

  9. Evaluation of an Automated Information Extraction Tool for Imaging Data Elements to Populate a Breast Cancer Screening Registry.

    Science.gov (United States)

    Lacson, Ronilda; Harris, Kimberly; Brawarsky, Phyllis; Tosteson, Tor D; Onega, Tracy; Tosteson, Anna N A; Kaye, Abby; Gonzalez, Irina; Birdwell, Robyn; Haas, Jennifer S

    2015-10-01

    Breast cancer screening is central to early breast cancer detection. Identifying and monitoring process measures for screening is a focus of the National Cancer Institute's Population-based Research Optimizing Screening through Personalized Regimens (PROSPR) initiative, which requires participating centers to report structured data across the cancer screening continuum. We evaluate the accuracy of automated information extraction of imaging findings from radiology reports, which are available as unstructured text. We present prevalence estimates of imaging findings for breast imaging received by women who obtained care in a primary care network participating in PROSPR (n = 139,953 radiology reports) and compared automatically extracted data elements to a "gold standard" based on manual review for a validation sample of 941 randomly selected radiology reports, including mammograms, digital breast tomosynthesis, ultrasound, and magnetic resonance imaging (MRI). The prevalence of imaging findings vary by data element and modality (e.g., suspicious calcification noted in 2.6% of screening mammograms, 12.1% of diagnostic mammograms, and 9.4% of tomosynthesis exams). In the validation sample, the accuracy of identifying imaging findings, including suspicious calcifications, masses, and architectural distortion (on mammogram and tomosynthesis); masses, cysts, non-mass enhancement, and enhancing foci (on MRI); and masses and cysts (on ultrasound), range from 0.8 to1.0 for recall, precision, and F-measure. Information extraction tools can be used for accurate documentation of imaging findings as structured data elements from text reports for a variety of breast imaging modalities. These data can be used to populate screening registries to help elucidate more effective breast cancer screening processes.

  10. Biomedical discovery acceleration, with applications to craniofacial development.

    Directory of Open Access Journals (Sweden)

    Sonia M Leach

    2009-03-01

    Full Text Available The profusion of high-throughput instruments and the explosion of new results in the scientific literature, particularly in molecular biomedicine, is both a blessing and a curse to the bench researcher. Even knowledgeable and experienced scientists can benefit from computational tools that help navigate this vast and rapidly evolving terrain. In this paper, we describe a novel computational approach to this challenge, a knowledge-based system that combines reading, reasoning, and reporting methods to facilitate analysis of experimental data. Reading methods extract information from external resources, either by parsing structured data or using biomedical language processing to extract information from unstructured data, and track knowledge provenance. Reasoning methods enrich the knowledge that results from reading by, for example, noting two genes that are annotated to the same ontology term or database entry. Reasoning is also used to combine all sources into a knowledge network that represents the integration of all sorts of relationships between a pair of genes, and to calculate a combined reliability score. Reporting methods combine the knowledge network with a congruent network constructed from experimental data and visualize the combined network in a tool that facilitates the knowledge-based analysis of that data. An implementation of this approach, called the Hanalyzer, is demonstrated on a large-scale gene expression array dataset relevant to craniofacial development. The use of the tool was critical in the creation of hypotheses regarding the roles of four genes never previously characterized as involved in craniofacial development; each of these hypotheses was validated by further experimental work.

  11. Biomedical discovery acceleration, with applications to craniofacial development.

    Science.gov (United States)

    Leach, Sonia M; Tipney, Hannah; Feng, Weiguo; Baumgartner, William A; Kasliwal, Priyanka; Schuyler, Ronald P; Williams, Trevor; Spritz, Richard A; Hunter, Lawrence

    2009-03-01

    The profusion of high-throughput instruments and the explosion of new results in the scientific literature, particularly in molecular biomedicine, is both a blessing and a curse to the bench researcher. Even knowledgeable and experienced scientists can benefit from computational tools that help navigate this vast and rapidly evolving terrain. In this paper, we describe a novel computational approach to this challenge, a knowledge-based system that combines reading, reasoning, and reporting methods to facilitate analysis of experimental data. Reading methods extract information from external resources, either by parsing structured data or using biomedical language processing to extract information from unstructured data, and track knowledge provenance. Reasoning methods enrich the knowledge that results from reading by, for example, noting two genes that are annotated to the same ontology term or database entry. Reasoning is also used to combine all sources into a knowledge network that represents the integration of all sorts of relationships between a pair of genes, and to calculate a combined reliability score. Reporting methods combine the knowledge network with a congruent network constructed from experimental data and visualize the combined network in a tool that facilitates the knowledge-based analysis of that data. An implementation of this approach, called the Hanalyzer, is demonstrated on a large-scale gene expression array dataset relevant to craniofacial development. The use of the tool was critical in the creation of hypotheses regarding the roles of four genes never previously characterized as involved in craniofacial development; each of these hypotheses was validated by further experimental work.

  12. Inexperienced clinicians can extract pathoanatomic information from MRI narrative reports with high reproducibility for use in research/quality assurance

    Directory of Open Access Journals (Sweden)

    Kent Peter

    2011-07-01

    Full Text Available Abstract Background Although reproducibility in reading MRI images amongst radiologists and clinicians has been studied previously, no studies have examined the reproducibility of inexperienced clinicians in extracting pathoanatomic information from magnetic resonance imaging (MRI narrative reports and transforming that information into quantitative data. However, this process is frequently required in research and quality assurance contexts. The purpose of this study was to examine inter-rater reproducibility (agreement and reliability among an inexperienced group of clinicians in extracting spinal pathoanatomic information from radiologist-generated MRI narrative reports. Methods Twenty MRI narrative reports were randomly extracted from an institutional database. A group of three physiotherapy students independently reviewed the reports and coded the presence of 14 common pathoanatomic findings using a categorical electronic coding matrix. Decision rules were developed after initial coding in an effort to resolve ambiguities in narrative reports. This process was repeated a further three times using separate samples of 20 MRI reports until no further ambiguities were identified (total n = 80. Reproducibility between trainee clinicians and two highly trained raters was examined in an arbitrary coding round, with agreement measured using percentage agreement and reliability measured using unweighted Kappa (k. Reproducibility was then examined in another group of three trainee clinicians who had not participated in the production of the decision rules, using another sample of 20 MRI reports. Results The mean percentage agreement for paired comparisons between the initial trainee clinicians improved over the four coding rounds (97.9-99.4%, although the greatest improvement was observed after the first introduction of coding rules. High inter-rater reproducibility was observed between trainee clinicians across 14 pathoanatomic categories over the

  13. Case study on the extraction of land cover information from the SAR image of a coal mining area

    Institute of Scientific and Technical Information of China (English)

    HU Zhao-ling; LI Hai-quan; DU Pei-jun

    2009-01-01

    In this study, analyses are conducted on the information features of a construction site, a cornfield and subsidence seeper land in a coal mining area with a synthetic aperture radar (SAR) image of medium resolution. Based on features of land cover of the coal mining area, on texture feature extraction and a selection method of a gray-level co-occurrence matrix (GLCM) of the SAR image, we propose in this study that the optimum window size for computing the GLCM is an appropriate sized window that can effectively distinguish different types of land cover. Next, a band combination was carried out over the text feature images and the band-filtered SAR image to secure a new multi-band image. After the transformation of the new image with principal component analysis, a classification is conducted selectively on three principal component bands with the most information. Finally, through training and experimenting with the samples, a better three-layered BP neural network was established to classify the SAR image. The results show that, assisted by texture information, the neural network classification improved the accuracy of SAR image clas-sification by 14.6%, compared with a classification by maximum likelihood estimation without texture information.

  14. Classification of Informal Settlements Through the Integration of 2d and 3d Features Extracted from Uav Data

    Science.gov (United States)

    Gevaert, C. M.; Persello, C.; Sliuzas, R.; Vosselman, G.

    2016-06-01

    Unmanned Aerial Vehicles (UAVs) are capable of providing very high resolution and up-to-date information to support informal settlement upgrading projects. In order to provide accurate basemaps, urban scene understanding through the identification and classification of buildings and terrain is imperative. However, common characteristics of informal settlements such as small, irregular buildings with heterogeneous roof material and large presence of clutter challenge state-of-the-art algorithms. Especially the dense buildings and steeply sloped terrain cause difficulties in identifying elevated objects. This work investigates how 2D radiometric and textural features, 2.5D topographic features, and 3D geometric features obtained from UAV imagery can be integrated to obtain a high classification accuracy in challenging classification problems for the analysis of informal settlements. It compares the utility of pixel-based and segment-based features obtained from an orthomosaic and DSM with point-based and segment-based features extracted from the point cloud to classify an unplanned settlement in Kigali, Rwanda. Findings show that the integration of 2D and 3D features leads to higher classification accuracies.

  15. CLASSIFICATION OF INFORMAL SETTLEMENTS THROUGH THE INTEGRATION OF 2D AND 3D FEATURES EXTRACTED FROM UAV DATA

    Directory of Open Access Journals (Sweden)

    C. M. Gevaert

    2016-06-01

    Full Text Available Unmanned Aerial Vehicles (UAVs are capable of providing very high resolution and up-to-date information to support informal settlement upgrading projects. In order to provide accurate basemaps, urban scene understanding through the identification and classification of buildings and terrain is imperative. However, common characteristics of informal settlements such as small, irregular buildings with heterogeneous roof material and large presence of clutter challenge state-of-the-art algorithms. Especially the dense buildings and steeply sloped terrain cause difficulties in identifying elevated objects. This work investigates how 2D radiometric and textural features, 2.5D topographic features, and 3D geometric features obtained from UAV imagery can be integrated to obtain a high classification accuracy in challenging classification problems for the analysis of informal settlements. It compares the utility of pixel-based and segment-based features obtained from an orthomosaic and DSM with point-based and segment-based features extracted from the point cloud to classify an unplanned settlement in Kigali, Rwanda. Findings show that the integration of 2D and 3D features leads to higher classification accuracies.

  16. Resource Conservation and Recovery Information System extract tape. Data tape documentation

    Energy Technology Data Exchange (ETDEWEB)

    1990-12-31

    Within the Environmental Protection Agency (EPA), the Office of Solid Waste and Emergency Response (OSWER) is responsible for the development and management of a national program to safely handle solid and hazardous waste. The national program, for the most part, is authorized by the Resource Conservation and Recovery Act (RCRA). The Hazardous Waste Data Management System (HWDMS) was developed to automatically track the status of permits, reports, inspections, enforcement activities, and financial data to assist EPA in managing the data generated by RCRA. As with many computer systems, HWDMS has outgrown its capabilities, so a new system is needed. The new system is called the Resource Conservation and Recovery Information System (RCRIS). The goal of the RCRIS system is to provide a more effective means for tracking hazardous waste handlers regulated under RCRA. RCRA Notification, Permitting, and Compliance Monitoring and Evaluation data is available through the National Technical Information Service (NTIS) on IBM compatible tapes. From now until HWDMS is completely archived, there will be two data tapes from NTIS. There will be a tape for HWDMS and a separate one for RCRIS. The HWDMS tape will include data from all States and Territories, except for Mississippi. The RCRIS tape will only contain the data from Mississippi and general enforcement data, sensitive information is not included.

  17. All India Seminar on Biomedical Engineering 2012

    CERN Document Server

    Bhatele, Mukta

    2013-01-01

    This book is a collection of articles presented by researchers and practitioners, including engineers, biologists, health professionals and informatics/computer scientists, interested in both theoretical advances and applications of information systems, artificial intelligence, signal processing, electronics and other engineering tools in areas related to biology and medicine in the All India Seminar on Biomedical Engineering 2012 (AISOBE 2012), organized by The Institution of Engineers (India), Jabalpur Local Centre, Jabalpur, India during November 3-4, 2012. The content of the book is useful to doctors, engineers, researchers and academicians as well as industry professionals.

  18. You had me at "Hello": Rapid extraction of dialect information from spoken words.

    Science.gov (United States)

    Scharinger, Mathias; Monahan, Philip J; Idsardi, William J

    2011-06-15

    Research on the neuronal underpinnings of speaker identity recognition has identified voice-selective areas in the human brain with evolutionary homologues in non-human primates who have comparable areas for processing species-specific calls. Most studies have focused on estimating the extent and location of these areas. In contrast, relatively few experiments have investigated the time-course of speaker identity, and in particular, dialect processing and identification by electro- or neuromagnetic means. We show here that dialect extraction occurs speaker-independently, pre-attentively and categorically. We used Standard American English and African-American English exemplars of 'Hello' in a magnetoencephalographic (MEG) Mismatch Negativity (MMN) experiment. The MMN as an automatic change detection response of the brain reflected dialect differences that were not entirely reducible to acoustic differences between the pronunciations of 'Hello'. Source analyses of the M100, an auditory evoked response to the vowels suggested additional processing in voice-selective areas whenever a dialect change was detected. These findings are not only relevant for the cognitive neuroscience of language, but also for the social sciences concerned with dialect and race perception.

  19. Multiple energy synchrotron biomedical imaging system

    Science.gov (United States)

    Bassey, B.; Martinson, M.; Samadi, N.; Belev, G.; Karanfil, C.; Qi, P.; Chapman, D.

    2016-12-01

    A multiple energy imaging system that can extract multiple endogenous or induced contrast materials as well as water and bone images would be ideal for imaging of biological subjects. The continuous spectrum available from synchrotron light facilities provides a nearly perfect source for multiple energy x-ray imaging. A novel multiple energy x-ray imaging system, which prepares a horizontally focused polychromatic x-ray beam, has been developed at the BioMedical Imaging and Therapy bend magnet beamline at the Canadian Light Source. The imaging system is made up of a cylindrically bent Laue single silicon (5,1,1) crystal monochromator, scanning and positioning stages for the subjects, flat panel (area) detector, and a data acquisition and control system. Depending on the crystal’s bent radius, reflection type, and the horizontal beam width of the filtered synchrotron radiation (20-50 keV) used, the size and spectral energy range of the focused beam prepared varied. For example, with a bent radius of 95 cm, a (1,1,1) type reflection and a 50 mm wide beam, a 0.5 mm wide focused beam of spectral energy range 27 keV-43 keV was obtained. This spectral energy range covers the K-edges of iodine (33.17 keV), xenon (34.56 keV), cesium (35.99 keV), and barium (37.44 keV) some of these elements are used as biomedical and clinical contrast agents. Using the developed imaging system, a test subject composed of iodine, xenon, cesium, and barium along with water and bone were imaged and their projected concentrations successfully extracted. The estimated dose rate to test subjects imaged at a ring current of 200 mA is 8.7 mGy s-1, corresponding to a cumulative dose of 1.3 Gy and a dose of 26.1 mGy per image. Potential biomedical applications of the imaging system will include projection imaging that requires any of the extracted elements as a contrast agent and multi-contrast K-edge imaging.

  20. Linking attentional processes and conceptual problem solving: Visual cues facilitate the automaticity of extracting relevant information from diagrams

    Directory of Open Access Journals (Sweden)

    Amy eRouinfar

    2014-09-01

    Full Text Available This study investigated links between lower-level visual attention processes and higher-level problem solving. This was done by overlaying visual cues on conceptual physics problem diagrams to direct participants’ attention to relevant areas to facilitate problem solving. Participants (N = 80 individually worked through four problem sets, each containing a diagram, while their eye movements were recorded. Each diagram contained regions that were relevant to solving the problem correctly and separate regions related to common incorrect responses. Problem sets contained an initial problem, six isomorphic training problems, and a transfer problem. The cued condition saw visual cues overlaid on the training problems. Participants’ verbal responses were used to determine their accuracy. The study produced two major findings. First, short duration visual cues can improve problem solving performance on a variety of insight physics problems, including transfer problems not sharing the surface features of the training problems, but instead sharing the underlying solution path. Thus, visual cues can facilitate re-representing a problem and overcoming impasse, enabling a correct solution. Importantly, these cueing effects on problem solving did not involve the solvers’ attention necessarily embodying the solution to the problem. Instead, the cueing effects were caused by solvers attending to and integrating relevant information in the problems into a solution path. Second, these short duration visual cues when administered repeatedly over multiple training problems resulted in participants becoming more efficient at extracting the relevant information on the transfer problem, showing that such cues can improve the automaticity with which solvers extract relevant information from a problem. Both of these results converge on the conclusion that lower-order visual processes driven by attentional cues can influence higher-order cognitive processes