1. 73-96 of 2811 « 1 2 3 4 5 6 7 ... 116 117 118 »
    1. Evaluating Terminologies to Enable Imaging-Related Decision Rule Sharing.

      Evaluating Terminologies to Enable Imaging-Related Decision Rule Sharing.

      AMIA Annu Symp Proc. 2016;2016:2082-2089

      Authors: Yan Z, Lacson R, Ip I, Valtchinov V, Raja A, Osterbur D, Khorasani R

      Abstract Purpose: Clinical decision support tools provide recommendations based on decision rules. A fundamental challenge regarding decision rule-sharing involves inadequate expression using standard terminology.

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    2. Entity recognition from clinical texts via recurrent neural network.

      Entity recognition from clinical texts via recurrent neural network.

      Entity recognition from clinical texts via recurrent neural network.

      BMC Med Inform Decis Mak. 2017 Jul 05;17(Suppl 2):67

      Authors: Liu Z, Yang M, Wang X, Chen Q, Tang B, Wang Z, Xu H

      Abstract BACKGROUND: Entity recognition is one of the most primary steps for text analysis and has long attracted considerable attention from researchers. In the clinical domain, various types of entities, such as clinical entities and protected health information (PHI), widely exist in clinical texts.

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    3. Detecting clinically relevant new information in clinical notes across specialties and settings.

      Detecting clinically relevant new information in clinical notes across specialties and settings.

      Detecting clinically relevant new information in clinical notes across specialties and settings.

      BMC Med Inform Decis Mak. 2017 Jul 05;17(Suppl 2):68

      Authors: Zhang R, Pakhomov SVS, Arsoniadis EG, Lee JT, Wang Y, Melton GB

      Abstract BACKGROUND: Automated methods for identifying clinically relevant new versus redundant information in electronic health record (EHR) clinical notes is useful for clinicians and researchers involved in patient care and clinical research, respectively.

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    4. Introduction: the International Conference on Intelligent Biology and Medicine (ICIBM) 2016: special focus on medical informatics and big data.

      Introduction: the International Conference on Intelligent Biology and Medicine (ICIBM) 2016: special focus on medical informatics and big data.

      Introduction: the International Conference on Intelligent Biology and Medicine (ICIBM) 2016: special focus on medical informatics and big data.

      BMC Med Inform Decis Mak. 2017 Jul 05;17(Suppl 2):77

      Authors: Tao C, Gong Y, Xu H, Zhao Z

      Abstract In this editorial, we first summarize the 2016 International Conference on Intelligent Biology and Medicine (ICIBM 2016) held on December 8-10, 2016 in Houston, Texas, USA, and then briefly introduce the ten research articles included in this supplement issue. At ICIBM 2016, a special theme, "Medical Informatics and Big Data," was dedicated to the recent advances of data science ...

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    5. Lightweight predicate extraction for patient-level cancer information and ontology development.

      Lightweight predicate extraction for patient-level cancer information and ontology development.

      Lightweight predicate extraction for patient-level cancer information and ontology development.

      BMC Med Inform Decis Mak. 2017 Jul 05;17(Suppl 2):73

      Authors: Amith M, Song HY, Zhang Y, Xu H, Tao C

      Abstract BACKGROUND: Knowledge engineering for ontological knowledgebases is resource and time intensive. To alleviate these issues, especially for novices, automated tools from the natural language domain can assist in the development process of ontologies.

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    6. An active learning-enabled annotation system for clinical named entity recognition.

      An active learning-enabled annotation system for clinical named entity recognition.

      An active learning-enabled annotation system for clinical named entity recognition.

      BMC Med Inform Decis Mak. 2017 Jul 05;17(Suppl 2):82

      Authors: Chen Y, Lask TA, Mei Q, Chen Q, Moon S, Wang J, Nguyen K, Dawodu T, Cohen T, Denny JC, Xu H

      Abstract BACKGROUND: Active learning (AL) has shown the promising potential to minimize the annotation cost while maximizing the performance in building statistical natural language processing (NLP) models.

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    7. The tool for the automatic analysis of lexical sophistication (TAALES): version 2.0.

      The tool for the automatic analysis of lexical sophistication (TAALES): version 2.0.

      The tool for the automatic analysis of lexical sophistication (TAALES): version 2.0.

      Behav Res Methods. 2017 Jul 11;:

      Authors: Kyle K, Crossley S, Berger C

      Abstract This study introduces the second release of the Tool for the Automatic Analysis of Lexical Sophistication (TAALES 2.0), a freely available and easy-to-use text analysis tool. TAALES 2.0 is housed on a user's hard drive (allowing for secure data processing) and is available on most operating systems (Windows, Mac, and Linux).

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    8. A Software Application for Mining and Presenting Relevant Cancer Clinical Trials per Cancer Mutation.

      A Software Application for Mining and Presenting Relevant Cancer Clinical Trials per Cancer Mutation.

      A Software Application for Mining and Presenting Relevant Cancer Clinical Trials per Cancer Mutation.

      Cancer Inform. 2017;16:1176935117711940

      Authors: Gandy LM, Gumm J, Blackford AL, Fertig EJ, Diaz LA

      Abstract ClinicalTrials.org is a popular portal which physicians use to find clinical trials for their patients. However, the current setup of ClinicalTrials.org makes it difficult for oncologists to locate clinical trials for patients based on mutational status.

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      Mentions: Egfr
    9. Leveraging syntax to better capture the semantics of elliptical coordinated compound noun phrases.

      Leveraging syntax to better capture the semantics of elliptical coordinated compound noun phrases.

      Leveraging syntax to better capture the semantics of elliptical coordinated compound noun phrases.

      J Biomed Inform. 2017 Jul 04;:

      Authors: Blake C, Rindflesch T

      Abstract Full-text scientific articles are increasingly available, but capturing the meaning conveyed within an article automatically remains a bottleneck for semantic search and reasoning systems. In this paper we consider elliptical coordinated compound noun phrases that authors use to save space in an article.

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    10. Comparison of Grouping Methods for Template Extraction from VA Medical Record Text.

      Comparison of Grouping Methods for Template Extraction from VA Medical Record Text.

      Comparison of Grouping Methods for Template Extraction from VA Medical Record Text.

      Stud Health Technol Inform. 2017;238:136-139

      Authors: Redd AM, Gundlapalli AV, Divita G, Tran LT, Pettey WBP, Samore MH

      Abstract We investigate options for grouping templates for the purpose of template identification and extraction from electronic medical records. We sampled a corpus of 1000 documents originating from Veterans Health Administration (VA) electronic medical record.

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    11. Using Structured and Unstructured Data to Refine Estimates of Military Sexual Trauma Status Among US Military Veterans.

      Using Structured and Unstructured Data to Refine Estimates of Military Sexual Trauma Status Among US Military Veterans.

      Using Structured and Unstructured Data to Refine Estimates of Military Sexual Trauma Status Among US Military Veterans.

      Stud Health Technol Inform. 2017;238:128-131

      Authors: Gundlapalli AV, Brignone E, Divita G, Jones AL, Redd A, Suo Y, Pettey WBP, Mohanty A, Gawron L, Blais R, Samore MH, Fargo JD

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    12. An Ontology-Enabled Natural Language Processing Pipeline for Provenance Metadata Extraction from Biomedical Text (Short Paper).

      An Ontology-Enabled Natural Language Processing Pipeline for Provenance Metadata Extraction from Biomedical Text (Short Paper).

      An Ontology-Enabled Natural Language Processing Pipeline for Provenance Metadata Extraction from Biomedical Text (Short Paper).

      On Move Meaningful Internet Syst. 2016 Oct;10033:699-708

      Authors: Valdez J, Rueschman M, Kim M, Redline S, Sahoo SS

      Abstract Extraction of structured information from biomedical literature is a complex and challenging problem due to the complexity of biomedical domain and lack of appropriate natural language processing (NLP) techniques.

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    13. Automatic prediction of coronary artery disease from clinical narratives.

      Automatic prediction of coronary artery disease from clinical narratives.

      Automatic prediction of coronary artery disease from clinical narratives.

      J Biomed Inform. 2017 Jun 26;:

      Authors: Buchan K, Filannino M, Uzuner Ö

      Abstract Coronary Artery Disease (CAD) is not only the most common form of heart disease, but also the leading cause of death in both men and women[1]. We present a system that is able to automatically predict whether patients develop coronary artery disease based on their narrative medical histories, i.e., clinical free text.

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      Mentions: CAD
    14. Mapping Between fMRI Responses to Movies and their Natural Language Annotations.

      Mapping Between fMRI Responses to Movies and their Natural Language Annotations.

      Mapping Between fMRI Responses to Movies and their Natural Language Annotations.

      Neuroimage. 2017 Jun 22;:

      Authors: Vodrahalli K, Chen PH, Liang Y, Baldassano C, Chen J, Yong E, Honey C, Hasson U, Ramadge P, Norman KA, Arora S

      Abstract Several research groups have shown how to map fMRI responses to the meanings of presented stimuli. This paper presents new methods for doing so when only a natural language annotation is available as the description of the stimulus.

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      Mentions: PCA
    15. Natural Language Processing for EHR-Based Pharmacovigilance: A Structured Review.

      Natural Language Processing for EHR-Based Pharmacovigilance: A Structured Review.

      Natural Language Processing for EHR-Based Pharmacovigilance: A Structured Review.

      Drug Saf. 2017 Jun 22;:

      Authors: Luo Y, Thompson WK, Herr TM, Zeng Z, Berendsen MA, Jonnalagadda SR, Carson MB, Starren J

      Abstract The goal of pharmacovigilance is to detect, monitor, characterize and prevent adverse drug events (ADEs) with pharmaceutical products.

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      Mentions: NLP EHR ADE
    16. Comparing Diagnostic Performance of Digital Breast Tomosynthesis and Full-Field Digital Mammography in a Hybrid Screening Environment.

      Comparing Diagnostic Performance of Digital Breast Tomosynthesis and Full-Field Digital Mammography in a Hybrid Screening Environment.

      Comparing Diagnostic Performance of Digital Breast Tomosynthesis and Full-Field Digital Mammography in a Hybrid Screening Environment.

      AJR Am J Roentgenol. 2017 Jun 22;:1-6

      Authors: Giess CS, Pourjabbar S, Ip IK, Lacson R, Alper E, Khorasani R

      Abstract OBJECTIVE: The purpose of this study is to compare the diagnostic performance of screening digital breast tomosynthesis (DBT) to that of full-field digital mammography (FFDM) in a mixed DBT and FFDM imaging environment.

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    17. Classifying Chinese Questions Related to Health Care Posted by Consumers Via the Internet.

      Classifying Chinese Questions Related to Health Care Posted by Consumers Via the Internet.

      Classifying Chinese Questions Related to Health Care Posted by Consumers Via the Internet.

      J Med Internet Res. 2017 Jun 20;19(6):e220

      Authors: Guo H, Na X, Hou L, Li J

      Abstract BACKGROUND: In question answering (QA) system development, question classification is crucial for identifying information needs and improving the accuracy of returned answers. Although the questions are domain-specific, they are asked by non-professionals, making the question classification task more challenging.

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    18. Natural Language Processing for Asthma Ascertainment in Different Practice Settings.

      Natural Language Processing for Asthma Ascertainment in Different Practice Settings.

      Natural Language Processing for Asthma Ascertainment in Different Practice Settings.

      J Allergy Clin Immunol Pract. 2017 Jun 17;:

      Authors: Wi CI, Sohn S, Ali M, Krusemark E, Ryu E, Liu H, Juhn YJ

      Abstract BACKGROUND: We developed and validated NLP-PAC, a natural language processing (NLP) algorithm based on predetermined asthma criteria (PAC) for asthma ascertainment using electronic health records at Mayo Clinic.

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      Mentions: Mayo Clinic NLP Liu
    19. Biomedical text mining for research rigor and integrity: tasks, challenges, directions.

      Biomedical text mining for research rigor and integrity: tasks, challenges, directions.

      Biomedical text mining for research rigor and integrity: tasks, challenges, directions.

      Brief Bioinform. 2017 Jun 13;:

      Authors: Kilicoglu H

      Abstract An estimated quarter of a trillion US dollars is invested in the biomedical research enterprise annually. There is growing alarm that a significant portion of this investment is wasted because of problems in reproducibility of research findings and in the rigor and integrity of research conduct and reporting.

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    20. What Are People Tweeting About Zika? An Exploratory Study Concerning Its Symptoms, Treatment, Transmission, and Prevention.

      What Are People Tweeting About Zika? An Exploratory Study Concerning Its Symptoms, Treatment, Transmission, and Prevention.

      What Are People Tweeting About Zika? An Exploratory Study Concerning Its Symptoms, Treatment, Transmission, and Prevention.

      JMIR Public Health Surveill. 2017 Jun 19;3(2):e38

      Authors: Miller M, Banerjee T, Muppalla R, Romine W, Sheth A

      Abstract BACKGROUND: In order to harness what people are tweeting about Zika, there needs to be a computational framework that leverages machine learning techniques to recognize relevant Zika tweets and, further, categorize these into disease-specific categories to address specific societal concerns related to the prevention, transmission, symptoms, and treatment of Zika virus. OBJECTIVE: The purpose of this study was to determine the relevancy ...

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    21. Data mining and pathway analysis of glucose-6-phosphate dehydrogenase with natural language processing.

      Data mining and pathway analysis of glucose-6-phosphate dehydrogenase with natural language processing.

      Data mining and pathway analysis of glucose-6-phosphate dehydrogenase with natural language processing.

      Mol Med Rep. 2017 Jun 15;:

      Authors: Chen L, Zhang C, Wang Y, Li Y, Han Q, Yang H, Zhu Y

      Abstract Human glucose-6-phosphate dehydrogenase (G6PD) is a crucial enzyme in the pentose phosphate pathway, and serves an important role in biosynthesis and the redox balance.

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      Mentions: Yang H Li Y
    73-96 of 2811 « 1 2 3 4 5 6 7 ... 116 117 118 »
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      Discourse, Entailment, Machine Translation, NER, Parsing, Segmentation, Semantic, Sentiment, Summarization, WSD