Predictive modeling of addiction lapses in a mobile health application

Computer Science

• Modeling 100%
• Mobile Health Application 100%
• Models 100%
• Survey 50%
• Events 50%
• Validation 50%
• Predictability 50%
• Characteristic Curve 50%
• Residential Treatment 50%
• Fold Cross Validation 50%
• Monitoring Service 50%
• Smartphone Application 50%
• Bayesian Network Model 50%

Medicine and Dentistry

• Patient 100%
• Addictive Behavior 100%
• Mobile Health 100%
• Health 66%
• Alcoholic Polyneuropathy 66%
• Therapeutic Procedure 33%
• Motivation 33%
• Health Care Cost 33%
• Family 33%
• Relapse 33%
• Self Monitoring 33%

Psychology

• Health 100%
• Predictive Modeling 100%
• Goals 33%
• Treatment 33%
• Alcohol 33%
• Specificity 33%
• Self-Monitoring 33%
• Network Model 33%
• Alcoholism 33%
• Smartphone 33%
• Cross-Validation 33%