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A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts
Published on: September 20, 2018
askMEDLINE: a free-text, natural language query tool for MEDLINE/PubMed
Paul Fontelo1, Fang Liu, Michael Ackerman
1Office of High Performance Computing and Communications, National Library of Medicine, 8600 Rockville Pike, Bethesda, Maryland 20894, USA. fontelo@nlm.nih.gov
Background:
Plain language search tools for MEDLINE/PubMed are few. We wanted to develop a search tool that would allow anyone using a free-text, natural language query and without knowing specialized vocabularies that an expert searcher might use, to find relevant citations in MEDLINE/PubMed. This tool would translate a question into an efficient search.
Results:
The accuracy and relevance of retrieved citations were compared to references cited in BMJ POEMs and CATs (critically appraised topics) questions from the University of Michigan Department of Pediatrics. askMEDLINE correctly matched the cited references 75.8% in POEMs and 89.2 % in CATs questions on first pass. When articles that were deemed to be relevant to the clinical questions were included, the overall efficiency in retrieving journal articles was 96.8% (POEMs) and 96.3% (CATs.)
Conclusion:
askMEDLINE might be a useful search tool for clinicians, researchers, and other information seekers interested in finding current evidence in MEDLINE/PubMed. The text-only format could be convenient for users with wireless handheld devices and those with low-bandwidth connections in remote locations.
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