Using Implicit Information to Identify Smoking Status in Smoke-blind Medical Discharge Summaries

Journal of the American Medical Informatics Association

Volumn 15, Issue 1, 2008, Pages 29-31

  Wicentowski, Richard ^a   Sydes, Matthew R ^b  

^a SWARTHMORE COLLEGE   (United States)

^b MRC CLINICAL TRIALS UNIT   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

ACCURACY; ARTICLE; BAYES THEOREM; FEASIBILITY STUDY; HOSPITAL DISCHARGE; HUMAN; MEDICAL INFORMATION; MEDICAL RECORD; SMOKING;

BAYES THEOREM; CLASSIFICATION; DATABASES, FACTUAL; HUMANS; MEDICAL RECORDS SYSTEMS, COMPUTERIZED; PATIENT DISCHARGE; SMOKING;

EID: 36749066006     PISSN: 10675027     EISSN: None     Source Type: Journal    
DOI: 10.1197/jamia.M2440     Document Type: Article

References (6)

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3. Chapman W.W., Bridewell W., Hanbury P., Cooper G.F., and Buchanan B.G. A simple algorithm for identifying negated findings and diseases in discharge summaries. J Biomed Inform 34 (2001) 301-310
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6. Wicentowski R., and Sydes M.R. Identifying smoking status from implicit information in medical discharge summaries. i2b2 Workshop on Natural Language Processing Challenges for Clinical Records. Proc AMIA Annu Fall Symp (2006)