Document Detail


Medical knowledge discovery and management.
MedLine Citation:
PMID:  19562958     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
Although the volume of medical information is growing rapidly, the ability to rapidly convert this data into "actionable insights" and new medical knowledge is lagging far behind. The first step in the knowledge discovery process is data management and integration, which logically can be accomplished through the application of data warehouse technologies. A key insight that arises from efforts in biosurveillance and the global scope of military medicine is that information must be integrated over both time (longitudinal health records) and space (spatial localization of health-related events). Once data are compiled and integrated it is essential to encode the semantics and relationships among data elements through the use of ontologies and semantic web technologies to convert data into knowledge. Medical images form a special class of health-related information. Traditionally knowledge has been extracted from images by human observation and encoded via controlled terminologies. This approach is rapidly being replaced by quantitative analyses that more reliably support knowledge extraction. The goals of knowledge discovery are the improvement of both the timeliness and accuracy of medical decision making and the identification of new procedures and therapies.
Authors:
Fred Prior
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Publication Detail:
Type:  Journal Article    
Journal Detail:
Title:  Military medicine     Volume:  174     ISSN:  0026-4075     ISO Abbreviation:  Mil Med     Publication Date:  2009 May 
Date Detail:
Created Date:  2009-06-30     Completed Date:  2009-12-15     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  2984771R     Medline TA:  Mil Med     Country:  United States    
Other Details:
Languages:  eng     Pagination:  21-6     Citation Subset:  IM    
Affiliation:
Electronic Radiology Laboratory, Mallinckrodt Institute of Radiology, Washington University School of Medicine, 4525 Scott Avenue, St. Louis, MO 63110, USA.
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MeSH Terms
Descriptor/Qualifier:
Access to Information*
Artificial Intelligence
Female
Health Knowledge, Attitudes, Practice*
Hospital Information Systems / organization & administration*
Humans
Information Dissemination*
Information Storage and Retrieval*
Male
Medical Records Systems, Computerized / organization & administration*
Military Medicine
Military Personnel
Semantics
United States

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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