| An investigation into the feasibility of spoken clinical question answering. | |
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MedLine Citation:
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PMID: 22195154 Owner: NLM Status: In-Data-Review |
Abstract/OtherAbstract:
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Spoken question answering for clinical decision support is a potentially revolutionary technology for improving the efficiency and quality of health care delivery. This application involves many technologies currently being researched, including automatic speech recognition (ASR), information retrieval (IR), and summarization, all in the biomedical domain. In certain domains, the problem of spoken document retrieval has been declared solved because of the robustness of IR to ASR errors. This study investigates the extent to which spoken medical question answering benefits from that same robustness. We used the best results from previous speech recognition experiments as inputs to a clinical question answering system, and had physicians perform blind evaluations of results generated both by ASR transcripts of questions and gold standard transcripts of the same questions. Our results suggest that the medical domain differs enough from the open domain to require additional work in automatic speech recognition adapted for the biomedical domain. |
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Authors:
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Tim Miller; James J Cimino; Kourosh Ravvaz; Hong Yu |
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Publication Detail:
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Type: Journal Article Date: 2011-10-22 |
Journal Detail:
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Title: AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium Volume: 2011 ISSN: 1942-597X ISO Abbreviation: AMIA Annu Symp Proc Publication Date: 2011 |
Date Detail:
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Created Date: 2011-12-23 Completed Date: - Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 101209213 Medline TA: AMIA Annu Symp Proc Country: United States |
Other Details:
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Languages: eng Pagination: 954-9 Citation Subset: IM |
Affiliation:
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College of Health Sciences, University of Wisconsin - Milwaukee, Milwaukee, WI. |
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From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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