Show simple item record

dc.contributor.authorAdams, Clive E.
dc.date.accessioned2017-10-31T11:41:15Z
dc.date.available2017-10-31T11:41:15Z
dc.date.issued2010
dc.identifier.citationCohen, A. M., Adams, C. E., Davis, J. M., Yu, C., Yu, P. S., Meng, W., Duggan, L., McDonagh, M. & Smalheiser, N. R. (2010). Evidence-based medicine, the essential role of systematic reviews, and the need for automated text mining tools. In: Veinot, T., (Ed.) 1st ACM International Health Informatics Symposium, 11-12 November 2010 Virginia, United States. Ohio: Proceedings of the 1st ACM International Health Informatics Symposium, p.376-380.en
dc.identifier.other10.1145/1882992.1883046
dc.identifier.urihttp://hdl.handle.net/20.500.12904/10803
dc.description.abstractHigh quality, cost-effective medical care requires consideration of the best available, most appropriate evidence in the care of each patient, a practice known as Evidence-based Medicine (EBM). EBM is dependent upon the wide availability and coverage of accurate, objective syntheses called evidence reports (also called systematic reviews). These are compiled by a time and resource-intensive process that is largely manual, and that has not taken advantage of many of the advances in information processing technologies that have assisted other textual domains. We propose a specific text-mining based pipeline to support the creation and updating of evidence reports that provides support for the literature collection, collation, and triage steps of the systematic review process. The pipeline includes a metasearch engine that covers both bibliographic databases and selected "grey" literature; a module that classifies articles according to study type; a module for grouping studies that are closely related (e.g. that derive from the same underlying clinical trial or same study cohort); and an automated system that ranks publications according to the likelihood that they will meet inclusion criteria for the report. The proposed pipeline will also enable groups performing systematic review to reuse tools and models created by other groups, and will provide a test-bed for further informatics research to develop improved tools in the future. Ultimately, this should increase the rate that high-quality systematic reviews and meta-analyses can be generated, accessed and utilized by clinicians, patients, care-givers, and policymakers, resulting in better and more cost-effective care.
dc.description.urihttps://dl.acm.org/citation.cfm?id=1883046
dc.subjectEvidence-based practiceen
dc.subjectInformation storage and retrievalen
dc.titleEvidence-based medicine, the essential role of systematic reviews, and the need for automated text mining toolsen
dc.typeConference Proceeding
html.description.abstractHigh quality, cost-effective medical care requires consideration of the best available, most appropriate evidence in the care of each patient, a practice known as Evidence-based Medicine (EBM). EBM is dependent upon the wide availability and coverage of accurate, objective syntheses called evidence reports (also called systematic reviews). These are compiled by a time and resource-intensive process that is largely manual, and that has not taken advantage of many of the advances in information processing technologies that have assisted other textual domains. We propose a specific text-mining based pipeline to support the creation and updating of evidence reports that provides support for the literature collection, collation, and triage steps of the systematic review process. The pipeline includes a metasearch engine that covers both bibliographic databases and selected "grey" literature; a module that classifies articles according to study type; a module for grouping studies that are closely related (e.g. that derive from the same underlying clinical trial or same study cohort); and an automated system that ranks publications according to the likelihood that they will meet inclusion criteria for the report. The proposed pipeline will also enable groups performing systematic review to reuse tools and models created by other groups, and will provide a test-bed for further informatics research to develop improved tools in the future. Ultimately, this should increase the rate that high-quality systematic reviews and meta-analyses can be generated, accessed and utilized by clinicians, patients, care-givers, and policymakers, resulting in better and more cost-effective care.


This item appears in the following Collection(s)

Show simple item record