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AskHERMES: An online question answering system for complex clinical questions

AskHERMES: An online question answering system for complex clinical questions

http://www.wikidata.org/entity/Q24607276

about

Usability survey of biomedical question answering systems Features of effective medical knowledge resources to support point of care learning: a focus group study Textual inference for eligibility criteria resolution in clinical trials Methods for Linking EHR Notes to Education Materials A framework for ontology-based question answering with application to parasite immunology Biomedical question answering using semantic relations Assisted knowledge discovery for the maintenance of clinical guidelines Text summarization as a decision support aid An investigation into the feasibility of spoken clinical question answering Formative evaluation of a patient-specific clinical knowledge summarization tool.Text summarization in the biomedical domain: a systematic review of recent research A characterization of clinical questions asked by rehabilitation therapists SimQ: real-time retrieval of similar consumer health questions.Semantic biomedical resource discovery: a Natural Language Processing framework.Classification of clinically useful sentences in clinical evidence resources.Classification of Clinically Useful Sentences in MEDLINE.Event Recognition Based on Deep Learning in Chinese Texts.Speed and accuracy of a point of care web-based knowledge resource for clinicians: a controlled crossover trial.Assessing cardiovascular drug safety for clinical decision-making.Olelo: a web application for intuitive exploration of biomedical literature.EliIE: An open-source information extraction system for clinical trial eligibility criteria.Text classification for assisting moderators in online health communities.Examining the role of MEDLINE as a patient care information resource: an analysis of data from the Value of Libraries study Detecting clinically related content in online patient posts.Evaluating Casama: Contextualized semantic maps for summarization of lung cancer studies.Semantic annotation of consumer health questions.First steps in automatic summarization of transcription factor properties for RegulonDB: classification of sentences about structural domains and regulated processes.Qcorp: an annotated classification corpus of Chinese health questions.

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P2860

AskHERMES: An online question answering system for complex clinical questions

http://www.wikidata.org/entity/Q24607276

description

2011 nî lūn-bûn

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2011 թուականի Ապրիլին հրատարակուած գիտական յօդուած

@hyw

2011 թվականի ապրիլին հրատարակված գիտական հոդված

@hy

2011年の論文

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2011年論文

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2011年論文

@zh-hant

2011年論文

@zh-hk

2011年論文

@zh-mo

2011年論文

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2011年论文

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name

AskHERMES: An online question answering system for complex clinical questions

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AskHERMES: An online question answering system for complex clinical questions

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AskHERMES: An online question answering system for complex clinical questions

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AskHERMES: An online question answering system for complex clinical questions

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AskHERMES: An online question answering system for complex clinical questions

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AskHERMES: An online question answering system for complex clinical questions

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J.JBI.2011.01.004

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Journal of Biomedical Informatics

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AskHERMES: An online question answering system for complex clinical questions

@en

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Andrew Bennett

http://www.w3.org/2001/XMLSchema#string

Feifan Liu

http://www.w3.org/2001/XMLSchema#string

Hong Yu

http://www.w3.org/2001/XMLSchema#string

John Ely

http://www.w3.org/2001/XMLSchema#string

Lamont Antieau

http://www.w3.org/2001/XMLSchema#string

Pippa Simpson

http://www.w3.org/2001/XMLSchema#string

YongGang Cao

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P2860

Answers to questions posed during daily patient care are more likely to be answered by UpToDate than PubMed

Evaluation of PICO as a knowledge representation for clinical questions

Textpresso: an ontology-based information retrieval and extraction system for biological literature

Learning radiology a survey investigating radiology resident use of textbooks, journals, and the internet

Facilitating physicians' access to information via tailored text summarization

Effective mapping of biomedical text to the UMLS Metathesaurus: the MetaMap program

Exploring supervised and unsupervised methods to detect topics in biomedical text.

Factors associated with success in searching MEDLINE and applying evidence to answer clinical questions

Automatically extracting information needs from Ad Hoc clinical questions.

Customization in a unified framework for summarizing medical literature.

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277-88

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4298891

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10.1016/J.JBI.2011.01.004

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2

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44

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James J. Cimino

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2011-04-01T00:00:00Z

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49776292

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21256977

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question answering

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3433744

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