Using Artificial Intelligence Algorithms to Predict Self-Reported Problem Gambling Among Online Casino Gamblers from Different Countries Using Account-Based Player Data.

The prevalence of online gambling and the potential for related harm necessitate predictive models for early detection of problem gambling. The present study expands upon prior research by incorporating a cross-country approach to predict self-reported problem gambling using player-tracking data in...

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Bibliographic Details

Published in:	International Journal of Mental Health & Addiction Vol. 24; no. 2; pp. 981 - 1004
Main Authors:	Hopfgartner, Niklas, Auer, Michael, Helic, Denis, Griffiths, Mark D.
Format:	Article
Published:	Springer Nature Apr2026
Subjects:	Compulsive gambling Compulsive gamblers Artificial intelligence Cross-cultural studies Machine learning Prediction models Internet gambling
Online Access:	View this record in EBSCOhost