This paper is in the following e-collection/theme issue:

Mobile Health (mhealth) (3557) Digital Biomarkers and Digital Phenotyping (301) Methods and New Tools in Mental Health Research (572) Mobile Health in Psychiatry (545) Depression and Mood Disorders; Suicide Prevention (1730) Applications of AI (313) Mental Health Issues in Adolescence (660)

Published on in Vol 28 (2026)

This is a member publication of Imperial College London (Jisc)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/72501, first published .
Digital Phenotyping for Adolescent Mental Health: Feasibility Study Using Machine Learning to Predict Mental Health Risk From Active and Passive Smartphone Data

Digital Phenotyping for Adolescent Mental Health: Feasibility Study Using Machine Learning to Predict Mental Health Risk From Active and Passive Smartphone Data

Digital Phenotyping for Adolescent Mental Health: Feasibility Study Using Machine Learning to Predict Mental Health Risk From Active and Passive Smartphone Data

Authors of this article:

Balasundaram Kadirvelu1 Author Orcid Image ;   Teresa Bellido Bel2 Author Orcid Image ;   Aglaia Freccero2 Author Orcid Image ;   Martina Di Simplico2 Author Orcid Image ;   Dasha Nicholls2 Author Orcid Image ;   A Aldo Faisal1, 3 Author Orcid Image
Article Authors Cited by (2) Tweetations (2) Metrics

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  1. Zeng Z, Zhang Y, Zhu F. Proceedings of the 2025 International Conference on Artificial Intelligence, Virtual Reality and Interaction Design. Research and Development of a Youth Psychological Counseling System Based on Large Models and Anime Representation View
  2. Ponnuchamy K, Bharathi S, Nadeem S, P S, Shahid S, Bala N. 2025 International Conference on Sustainable Communication Networks and Application (ICSCN). New Parent App : A Mobile based Baby Growth and Milestone Tracker with Chatbot Support View