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Automatic indexing and retrieval of encounter-specific evidence for point-of-care support

O'Sullivan, Dympna M., Wilk, Szymon A., Michalowski, Wojtek J. and Farion, Ken J. (2010) Automatic indexing and retrieval of encounter-specific evidence for point-of-care support. Journal of Biomedical Informatics, 43 (4). pp. 623-631. ISSN 1532-0464

Full text not available from this repository.
Official URL: http://dx.doi.org/10.1016/j.jbi.2010.03.003

Abstract

Evidence-based medicine relies on repositories of empirical research evidence that can be used to support clinical decision making for improved patient care. However, retrieving evidence from such repositories at local sites presents many challenges. This paper describes a methodological framework for automatically indexing and retrieving empirical research evidence in the form of the systematic reviews and associated studies from The Cochrane Library, where retrieved documents are specific to a patient–physician encounter and thus can be used to support evidence-based decision making at the point of care. Such an encounter is defined by three pertinent groups of concepts – diagnosis, treatment, and patient, and the framework relies on these three groups to steer indexing and retrieval of reviews and associated studies. An evaluation of the indexing and retrieval components of the proposed framework was performed using documents relevant for the pediatric asthma domain. Precision and recall values for automatic indexing of systematic reviews and associated studies were 0.93 and 0.87, and 0.81 and 0.56, respectively. Moreover, precision and recall for the retrieval of relevant systematic reviews and associated studies were 0.89 and 0.81, and 0.92 and 0.89, respectively. With minor modifications, the proposed methodological framework can be customized for other evidence repositories.

Item Type: Article
Subjects: Q Science > QA Mathematics > Electronic computers. Computer science
T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science
Q Science > QA Mathematics > Computer software
T Technology > T Technology (General) > Information Technology > Computer software
R Medicine > Healthcare Industry
Divisions: School of Computing > Staff Research and Publications
Depositing User: Caoimhe Ní Mhaicín
Date Deposited: 22 Sep 2018 09:50
Last Modified: 22 Sep 2018 09:50
URI: https://norma.ncirl.ie/id/eprint/3174

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