Addictive Disorder Susceptibility Prediction Using Machine Learning Approaches

Abstract

This study explores the use of machine learning approaches for addiction prediction. Addiction is a major public health problem, and there is a need for reliable methods of predicting which individuals are at risk for developing substance use disorders. Machine learning has emerged as a powerful tool for predictive modelling, and has been applied successfully to a variety of tasks in the field of medicine. A proposed Machine Learning model for addiction prediction from an ongoing study is presented in this paper.