Accuracy of an automated knowledge base for identifying drug adverse reactions

Journal of Biomedical Informatics

Volumn 66, Issue , 2017, Pages 72-81

  Voss, E A ^a,b,c   Boyce, R D ^c,d   Ryan, P B ^a,c,e   van der Lei, J ^b,c   Rijnbeek, P R ^b,c   Schuemie, M J ^a,c  

^a JANSSEN RESEARCH AND DEVELOPMENT   (United States)

^b ERASMUS MEDICAL CENTER   (Netherlands)

^c Observational Health Data Sciences and Informatics   (United States)

^d UNIVERSITY OF PITTSBURGH   (United States)

^e Howard Hughes Medical Institute   (United States)

Author keywords

Adverse drug reaction; Health outcome; Knowledge base; Machine learning experiment; Pharmacovigilance

Indexed keywords

CLASSIFICATION (OF INFORMATION); DATA HANDLING; KNOWLEDGE BASED SYSTEMS; LEARNING SYSTEMS; PHARMACODYNAMICS;

ADVERSE DRUG REACTIONS; AUTOMATED DATA PROCESSING; HEALTH OUTCOMES; KNOWLEDGE BASE; PHARMACOVIGILANCE; PILOT IMPLEMENTATION; RECEIVER OPERATOR CURVES; SOURCES OF INFORMATIONS;

DRUG PRODUCTS;

AREA UNDER THE CURVE; ARTICLE; AUTOMATION; CLASSIFIER; CONTROLLED STUDY; KNOWLEDGE BASE; MACHINE LEARNING; PREDICTION; PRIORITY JOURNAL; SOFTWARE; ADVERSE DRUG REACTION; DRUG SURVEILLANCE PROGRAM; HUMAN; INFORMATION PROCESSING;

ADVERSE DRUG REACTION REPORTING SYSTEMS; AUTOMATIC DATA PROCESSING; DRUG-RELATED SIDE EFFECTS AND ADVERSE REACTIONS; HUMANS; KNOWLEDGE BASES; PHARMACOVIGILANCE;

EID: 85008622502     PISSN: 15320464     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jbi.2016.12.005     Document Type: Article

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