Development, implementation, and a cognitive evaluation of a definitional question answering system for physicians

Hong Yu, Minsuk Lee, David Kaufman, John Ely, Jerome A. Osheroff, George Hripcsak, James Cimino

Research output: Contribution to journalArticlepeer-review

65 Scopus citations

Abstract

The published medical literature and online medical resources are important sources to help physicians make patient treatment decisions. Traditional sources used for information retrieval (e.g., PubMed) often return a list of documents in response to a user's query. Frequently the number of returned documents from large knowledge repositories is large and makes information seeking practical only "after hours" and not in the clinical setting. This study developed novel algorithms, and designed, implemented, and evaluated a medical definitional question answering system (MedQA). MedQA automatically analyzed a large number of electronic documents to generate short and coherent answers in response to definitional questions (i.e., questions with the format of "What is X?"). Our preliminary cognitive evaluation shows that MedQA out-performed three other online information systems (Google, OneLook, and PubMed) in two important efficiency criteria; namely, time spent and number of actions taken for a physician to identify a definition. It is our contention that question answering systems that aggregate pertinent information scattered across different documents have the potential to address clinical information needs within a timeframe necessary to meet the demands of clinicians.

Original languageEnglish (US)
Pages (from-to)236-251
Number of pages16
JournalJournal of Biomedical Informatics
Volume40
Issue number3
DOIs
StatePublished - Jun 2007
Externally publishedYes

Keywords

  • Evaluation
  • Information retrieval
  • Machine-learning
  • Question analysis
  • Question answering
  • Text summarization

ASJC Scopus subject areas

  • Computer Science Applications
  • Health Informatics

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