Corpus ID: 21689474

CLINIQA: A Machine Intelligence Based Clinical Question Answering System

  title={CLINIQA: A Machine Intelligence Based Clinical Question Answering System},
  author={M. Zahid and A. Mittal and R. Joshi and G. Atluri},
  • M. Zahid, A. Mittal, +1 author G. Atluri
  • Published 2018
  • Computer Science
  • ArXiv
  • The recent developments in the field of biomedicine have made large volumes of biomedical literature available to the medical practitioners. Due to the large size and lack of efficient searching strategies, medical practitioners struggle to obtain necessary information available in the biomedical literature. Moreover, the most sophisticated search engines of age are not intelligent enough to interpret the clinicians' questions. These facts reflect the urgent need of an information retrieval… CONTINUE READING


    Towards a Medical Question-Answering System: a Feasibility Study
    • 81
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    Knowledge Extraction for Clinical Question Answering: Preliminary Results
    • 49
    • PDF
    Effective mapping of biomedical text to the UMLS Metathesaurus: the MetaMap program
    • 1,882
    • Highly Influential
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    Answering Clinical Questions with Role Identification
    • 55
    • PDF
    Classifying Medical Questions based on an Evidence Taxonomy
    • 41
    • PDF
    Evaluation of biomedical text-mining systems: Lessons learned from information retrieval
    • W. Hersh
    • Medicine, Computer Science
    • Briefings Bioinform.
    • 2005
    • 62
    • PDF
    Question answering in biomedicine
    • 40
    • Highly Influential
    • PDF
    Answering clinical questions.
    • 130
    Analysis of Statistical Question Classification for Fact-Based Questions
    • 142
    • PDF