The application of machine learning techniques as an adjunct to clinical decision making in alcohol dependence treatment

Substance Use and Misuse

Volumn 42, Issue 14, 2007, Pages 2193-2206

  Connor, J P ^a,b   Symons, M ^a,b   Feeney, G F X ^b   Young, R Mcd ^b,c   Wiles, J ^a  

^a UNIVERSITY OF QUEENSLAND   (Australia)

^b PRINCESS ALEXANDRA HOSPITAL   (Australia)

^c QUEENSLAND UNIVERSITY OF TECHNOLOGY   (Australia)

Author keywords

Alcohol treatment; Bayesian; Decision tree; Machine learning

Indexed keywords

ACAMPROSATE;

ABSTINENCE; ALCOHOL CONSUMPTION; ALCOHOLISM; ARTICLE; BAYES THEOREM; CLINICAL DECISION MAKING; CLINICAL TRIAL; COGNITIVE THERAPY; CONTROLLED CLINICAL TRIAL; CONTROLLED STUDY; DEMOGRAPHY; DISEASE SEVERITY; HUMAN; MACHINE LEARNING; MAJOR CLINICAL STUDY; NONLINEAR SYSTEM; PREDICTION; PRIORITY JOURNAL; QUALITY OF LIFE; STATISTICAL MODEL; WITHDRAWAL SYNDROME;

ALCOHOL DETERRENTS; ALCOHOLISM; ARTIFICIAL INTELLIGENCE; BAYES THEOREM; COGNITIVE THERAPY; DECISION SUPPORT SYSTEMS, CLINICAL; DECISION TREES; HAWAII; HUMANS; OUTCOME ASSESSMENT (HEALTH CARE); PILOT PROJECTS; RECURRENCE; TAURINE;

EID: 37549069948     PISSN: 10826084     EISSN: 15322491     Source Type: Journal    
DOI: 10.1080/10826080701658125     Document Type: Article

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