1. 1-24 of 2830 1 2 3 4 ... 116 117 118 »
    1. Improving Terminology Mapping in Clinical Text with Context-Sensitive Spelling Correction.

      Improving Terminology Mapping in Clinical Text with Context-Sensitive Spelling Correction.

      Stud Health Technol Inform. 2017;235:241-245

      Authors: Dziadek J, Henriksson A, Duneld M

      Abstract The mapping of unstructured clinical text to an ontology facilitates meaningful secondary use of health records but is non-trivial due to lexical variation and the abundance of misspellings in hurriedly produced notes.

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    2. The Human Behaviour-Change Project: harnessing the power of artificial intelligence and machine learning for evidence synthesis and interpretation.

      The Human Behaviour-Change Project: harnessing the power of artificial intelligence and machine learning for evidence synthesis and interpretation.

      Implement Sci. 2017 Oct 18;12(1):121

      Authors: Michie S, Thomas J, Johnston M, Aonghusa PM, Shawe-Taylor J, Kelly MP, Deleris LA, Finnerty AN, Marques MM, Norris E, O'Mara-Eves A, West R

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      Mentions: BCI
    3. De-Identification of Medical Narrative Data.

      De-Identification of Medical Narrative Data.

      Stud Health Technol Inform. 2017;244:23-27

      Authors: Foufi V, Gaudet-Blavignac C, Chevrier R, Lovis C

      Abstract Maintaining data security and privacy in an era of cybersecurity is a challenge. The enormous and rapidly growing amount of health-related data available today raises numerous questions about data collection, storage, analysis, comparability and interoperability but also about data protection.

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    4. Mining comorbidity patterns using retrospective analysis of big collection of outpatient records.

      Mining comorbidity patterns using retrospective analysis of big collection of outpatient records.

      Health Inf Sci Syst. 2017 Dec;5(1):3

      Authors: Boytcheva S, Angelova G, Angelov Z, Tcharaktchiev D

      Abstract BACKGROUND: Studying comorbidities of disorders is important for detection and prevention. For discovering frequent patterns of diseases we can use retrospective analysis of population data, by filtering events with common properties and similar significance.

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      Mentions: Bulgaria
    5. Querying EHRs with a Semantic and Entity-Oriented Query Language.

      Querying EHRs with a Semantic and Entity-Oriented Query Language.

      Stud Health Technol Inform. 2017;235:121-125

      Authors: Lelong R, Soualmia L, Dahamna B, Griffon N, Darmoni SJ

      Abstract While the digitization of medical documents has greatly expanded during the past decade, health information retrieval has become a great challenge to address many issues in medical research.

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    6. Interspecies gene function prediction using semantic similarity.

      Interspecies gene function prediction using semantic similarity.

      Interspecies gene function prediction using semantic similarity.

      BMC Syst Biol. 2016 Dec 23;10(Suppl 4):121

      Authors: Yu G, Luo W, Fu G, Wang J

      Abstract BACKGROUND: Gene Ontology (GO) is a collaborative project that maintains and develops controlled vocabulary (or terms) to describe the molecular function, biological roles and cellular location of gene products in a hierarchical ontology. GO also provides GO annotations that associate genes with GO terms.

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      Mentions: Gene Ontology Mouse
    7. Assessing Behavioral Stages From Social Media Data.

      Assessing Behavioral Stages From Social Media Data.

      CSCW Conf Comput Support Coop Work. 2017 Feb-Mar;2017:1320-1333

      Authors: Liu J, Weitzman ER, Chunara R

      Abstract Important work rooted in psychological theory posits that health behavior change occurs through a series of discrete stages. Our work builds on the field of social computing by identifying how social media data can be used to resolve behavior stages at high resolution (e.g.

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      Mentions: Liu
    8. De-identification of medical records using conditional random fields and long short-term memory networks.

      De-identification of medical records using conditional random fields and long short-term memory networks.

      J Biomed Inform. 2017 Oct 12;:

      Authors: Jiang Z, Zhao C, He B, Guan Y, Jiang J

      Abstract The CEGS N-GRID 2016 Shared Task 1 in Clinical Natural Language Processing focuses on the de-identification of psychiatric evaluation records. This paper describes two participating systems of our team, based on conditional random fields (CRFs) and long short-term memory networks (LSTMs).

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    9. A method for named entity normalization in biomedical articles: application to diseases and plants.

      A method for named entity normalization in biomedical articles: application to diseases and plants.

      BMC Bioinformatics. 2017 Oct 13;18(1):451

      Authors: Cho H, Choi W, Lee H

      Abstract BACKGROUND: In biomedical articles, a named entity recognition (NER) technique that identifies entity names from texts is an important element for extracting biological knowledge from articles.

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    10. Segment convolutional neural networks (Seg-CNNs) for classifying relations in clinical notes.

      Segment convolutional neural networks (Seg-CNNs) for classifying relations in clinical notes.

      Segment convolutional neural networks (Seg-CNNs) for classifying relations in clinical notes.

      J Am Med Inform Assoc. 2017 Aug 31;:

      Authors: Luo Y, Cheng Y, Uzuner Ö, Szolovits P, Starren J

      Abstract We propose Segment Convolutional Neural Networks (Seg-CNNs) for classifying relations from clinical notes. Seg-CNNs use only word-embedding features without manual feature engineering.

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    11. A new synonym-substitution method to enrich the human phenotype ontology.

      A new synonym-substitution method to enrich the human phenotype ontology.

      A new synonym-substitution method to enrich the human phenotype ontology.

      BMC Bioinformatics. 2017 Oct 10;18(1):446

      Authors: Taboada M, Rodriguez H, Gudivada RC, Martinez D

      Abstract BACKGROUND: Named entity recognition is critical for biomedical text mining, where it is not unusual to find entities labeled by a wide range of different terms.

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    12. Automatable algorithms to identify nonmedical opioid use using electronic data: a systematic review.

      Automatable algorithms to identify nonmedical opioid use using electronic data: a systematic review.

      Automatable algorithms to identify nonmedical opioid use using electronic data: a systematic review.

      J Am Med Inform Assoc. 2017 Nov 01;24(6):1204-1210

      Authors: Canan C, Polinski JM, Alexander GC, Kowal MK, Brennan TA, Shrank WH

      Abstract Objective: Improved methods to identify nonmedical opioid use can help direct health care resources to individuals who need them.

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    13. NLPReViz: an interactive tool for natural language processing on clinical text.

      NLPReViz: an interactive tool for natural language processing on clinical text.

      NLPReViz: an interactive tool for natural language processing on clinical text.

      J Am Med Inform Assoc. 2017 Jul 22;:

      Authors: Trivedi G, Pham P, Chapman WW, Hwa R, Wiebe J, Hochheiser H

      Abstract The gap between domain experts and natural language processing expertise is a barrier to extracting understanding from clinical text. We describe a prototype tool for interactive review and revision of natural language processing models of binary concepts extracted from clinical notes.

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    14. Bullying in Virtual Learning Communities.

      Bullying in Virtual Learning Communities.

      Bullying in Virtual Learning Communities.

      Adv Exp Med Biol. 2017;989:211-216

      Authors: Nikiforos S, Tzanavaris S, Kermanidis KL

      Abstract Bullying through the internet has been investigated and analyzed mainly in the field of social media. In this paper, it is attempted to analyze bullying in the Virtual Learning Communities using Natural Language Processing (NLP) techniques, mainly in the context of sociocultural learning theories. Therefore four case studies took place.

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      Mentions: NLP
    15. Simplifying drug package leaflets written in Spanish by using word embedding.

      Simplifying drug package leaflets written in Spanish by using word embedding.

      Simplifying drug package leaflets written in Spanish by using word embedding.

      J Biomed Semantics. 2017 Sep 29;8(1):45

      Authors: Segura-Bedmar I, Martínez P

      Abstract BACKGROUND: Drug Package Leaflets (DPLs) provide information for patients on how to safely use medicines. Pharmaceutical companies are responsible for producing these documents.

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      Mentions: Martínez
    16. Mimvec: a deep learning approach for analyzing the human phenome.

      Mimvec: a deep learning approach for analyzing the human phenome.

      Mimvec: a deep learning approach for analyzing the human phenome.

      BMC Syst Biol. 2017 Sep 21;11(Suppl 4):76

      Authors: Gan M, Li W, Zeng W, Wang X, Jiang R

      Abstract BACKGROUND: The human phenome has been widely used with a variety of genomic data sources in the inference of disease genes. However, most existing methods thus far derive phenotype similarity based on the analysis of biomedical databases by using the traditional term frequency-inverse document frequency (TF-IDF) formulation.

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    17. Fact-based Visual Question Answering.

      Fact-based Visual Question Answering.

      FVQA: Fact-based Visual Question Answering.

      IEEE Trans Pattern Anal Mach Intell. 2017 Sep 19;:

      Authors: Wang P, Wu Q, Shen C, Dick A, Hengel AVD

      Abstract Visual Question Answering (VQA) has attracted much attention in both computer vision and natural language processing communities, not least because it offers insight into the relationships between two important sources of information.

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    18. Decoding the neural representation of story meanings across languages.

      Decoding the neural representation of story meanings across languages.

      Decoding the neural representation of story meanings across languages.

      Hum Brain Mapp. 2017 Sep 20;:

      Authors: Dehghani M, Boghrati R, Man K, Hoover J, Gimbel SI, Vaswani A, Zevin JD, Immordino-Yang MH, Gordon AS, Damasio A, Kaplan JT

      Abstract Drawing from a common lexicon of semantic units, humans fashion narratives whose meaning transcends that of their individual utterances.

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      Mentions: Farsi
    19. The Adverse Drug Reactions from Patient Reports in Social Media Project: Five Major Challenges to Overcome to Operationalize Analysis and Efficiently Support Pharmacovigilance Process.

      The Adverse Drug Reactions from Patient Reports in Social Media Project: Five Major Challenges to Overcome to Operationalize Analysis and Efficiently Support Pharmacovigilance Process.

      The Adverse Drug Reactions from Patient Reports in Social Media Project: Five Major Challenges to Overcome to Operationalize Analysis and Efficiently Support Pharmacovigilance Process.

      JMIR Res Protoc. 2017 Sep 21;6(9):e179

      Authors: Bousquet C, Dahamna B, Guillemin-Lanne S, Darmoni SJ, Faviez C, Huot C, Katsahian S, Leroux V, Pereira S, Richard C, Schück S, Souvignet J, Lillo-Le Louët A, Texier N

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      Mentions: Pereira
    20. Assigning factuality values to semantic relations extracted from biomedical research literature.

      Assigning factuality values to semantic relations extracted from biomedical research literature.

      Assigning factuality values to semantic relations extracted from biomedical research literature.

      PLoS One. 2017;12(7):e0179926

      Authors: Kilicoglu H, Rosemblat G, Rindflesch TC

      Abstract Biomedical knowledge claims are often expressed as hypotheses, speculations, or opinions, rather than explicit facts (propositions). Much biomedical text mining has focused on extracting propositions from biomedical literature.

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    21. The International Classification of Functioning, Disability and Health (ICF) in Electronic Health Records. A Systematic Literature Review.

      The International Classification of Functioning, Disability and Health (ICF) in Electronic Health Records. A Systematic Literature Review.

      The International Classification of Functioning, Disability and Health (ICF) in Electronic Health Records. A Systematic Literature Review.

      Appl Clin Inform. 2017 Sep 20;8(3):964-980

      Authors: Maritz R, Aronsky D, Prodinger B

      Abstract BACKGROUND: The International Classification of Functioning, Disability and Health (ICF) is the World Health Organization's standard for describing health and health-related states.

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    1-24 of 2830 1 2 3 4 ... 116 117 118 »
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      Discourse, Entailment, Machine Translation, NER, Parsing, Segmentation, Semantic, Sentiment, Summarization, WSD