Validating a strategy for psychosocial phenotyping using a large corpus of clinical text

Journal of the American Medical Informatics Association

Volumn 20, Issue E2, 2013, Pages

  Gundlapalli, Adi V ^a,b   Redd, Andrew ^a,b   Carter, Marjorie ^a,b   Divita, Guy ^a,b   Shen, Shuying ^a,b   Palmer, Miland ^a   Samore, Matthew H ^a,b  

^a VETERANS AFFAIRS MEDICAL CENTER   (United States)

^b UNIVERSITY OF UTAH SCHOOL OF MEDICINE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ACCURACY; ADDICTION SEVERITY INDEX; ALGORITHM; ARTICLE; DATA BASE; DOCUMENTATION; ELECTRONIC MEDICAL RECORD; EMERGENCY WARD; HEALTH CARE SYSTEM; HOMELESSNESS; HUMAN; ICD-9-CM; MACHINE LEARNING; MENTAL HEALTH; NATURAL LANGUAGE PROCESSING; PERFORMANCE; PHENOTYPE; PREVALENCE; PRIMARY MEDICAL CARE; SENSITIVITY ANALYSIS; SOCIAL PSYCHOLOGY; SOCIAL WORK; SUBSTANCE ABUSE;

CLINICAL INFORMATICS; HIGH THROUGH-PUT; NATURAL LANGUAGE PROCESSING; PATIENT PHENOTYPE; PSYCHOSOCIAL CONCEPTS;

ALGORITHMS; ELECTRONIC HEALTH RECORDS; HUMANS; NATURAL LANGUAGE PROCESSING; PHENOTYPE; PSYCHOLOGY; UNITED STATES; UNITED STATES DEPARTMENT OF VETERANS AFFAIRS;

EID: 84890453011     PISSN: 10675027     EISSN: 1527974X     Source Type: Journal    
DOI: 10.1136/amiajnl-2013-001946     Document Type: Article

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