Development of a Mobile Application Based on a Machine Learning Model to Identify Potential Cases of Smartphone Addiction in School-Aged Adolescents
Published in 2024 IEEE XXXI International Conference on Electronics, Electrical Engineering and Computing (INTERCON), 2025
This paper developed a mobile app using a 92% accurate machine learning model (logistic regression) to detect smartphone addiction in adolescents. The app, based on a survey and demographic data, offers real-time results for parents and educators, enabling early intervention.
Recommended citation: J. Delgado, J. Hurtado, F. Vasquez (2024). "Development of a Mobile Application Based on a Machine Learning Model to Identify Potential Cases of Smartphone Addiction in School-Aged Adolescents." IEEE. 1(1).
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