Predictive modeling of addiction lapses in a mobile health application

Journal of Substance Abuse Treatment

Volumn 46, Issue 1, 2014, Pages 29-35

  Chih, Ming Yuan ^a   Patton, Timothy ^a   McTavish, Fiona M ^a   Isham, Andrew J ^a   Judkins Fisher, Chris L ^a   Atwood, Amy K ^a   Gustafson, David H ^a  

^a UNIVERSITY OF WISCONSIN MADISON   (United States)

Author keywords

Alcoholism; Lapse prediction; Machine learning; MHealth; Relapse

Indexed keywords

ADDICTION COMPREHENSIVE HEALTH ENHANCEMENT SUPPORT SYSTEM; ADULT; ALCOHOLISM; ARTICLE; BAYESIAN LEARNING; COMPUTER PROGRAM; DECISION SUPPORT SYSTEM; FEMALE; HEALTH SURVEY; HUMAN; MACHINE LEARNING; MAJOR CLINICAL STUDY; MALE; MOBILE PHONE; PREDICTION; PRIORITY JOURNAL; RECEIVER OPERATING CHARACTERISTIC; RELAPSE; SELF MONITORING; SENSITIVITY AND SPECIFICITY; VALIDATION STUDY;

ALCOHOLISM; LAPSE PREDICTION; MACHINE LEARNING; MHEALTH; RELAPSE;

ADULT; ALCOHOLISM; BAYES THEOREM; CELLULAR PHONE; DECISION MAKING; FEMALE; HUMANS; MALE; MIDDLE AGED; MOBILE APPLICATIONS; MODELS, STATISTICAL; PREDICTIVE VALUE OF TESTS; RECURRENCE; ROC CURVE; SENSITIVITY AND SPECIFICITY; YOUNG ADULT;

EID: 84886775560     PISSN: 07405472     EISSN: 18736483     Source Type: Journal    
DOI: 10.1016/j.jsat.2013.08.004     Document Type: Article

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