Application of an empiric Bayesian data mining algorithm to reports of pancreatitis associated with atypical antipsychotics

Pharmacotherapy

Volumn 24, Issue 9, 2004, Pages 1122-1129

  Hauben, Manfred ^a,b,c  

^a PFIZER INC   (United States)

^b NEW YORK UNIVERSITY SCHOOL OF MEDICINE   (United States)

^c NEW YORK MEDICAL COLLEGE   (United States)

Author keywords

Adverse drug reactions; Computed assisted signal detection algorithm; Data mining; Drug safety; Pharmacovigilance

Indexed keywords

AMYLASE; CLOZAPINE; HALOPERIDOL; NEUROLEPTIC AGENT; OLANZAPINE; PANCREAS ENZYME; RISPERIDONE; TRIACYLGLYCEROL LIPASE;

ACUTE PANCREATITIS; ADVERSE DRUG REACTION; ALGORITHM; AMYLASE BLOOD LEVEL; ARTICLE; ARTIFICIAL NEURAL NETWORK; BAYES THEOREM; COMPUTER ANALYSIS; DATA ANALYSIS; DATA BASE; DATA MINING; DRUG INDUCED DISEASE; DRUG MONITORING; DRUG SAFETY; DRUG SURVEILLANCE PROGRAM; FOOD AND DRUG ADMINISTRATION; HEMORRHAGIC PANCREATITIS; HUMAN; PANCREATITIS; SIGNAL DETECTION; TRIACYLGLYCEROL LIPASE BLOOD LEVEL; UNITED STATES;

ADVERSE DRUG REACTION REPORTING SYSTEMS; ANTIPSYCHOTIC AGENTS; BAYES THEOREM; DIAGNOSIS, COMPUTER-ASSISTED; HUMANS; PANCREATITIS; POISSON DISTRIBUTION; RETROSPECTIVE STUDIES;

EID: 4344629388     PISSN: 02770008     EISSN: None     Source Type: Journal    
DOI: 10.1592/phco.24.13.1122.38098     Document Type: Article

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