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

Mobile Health (mhealth) (3556) Digital Biomarkers and Digital Phenotyping (299) Methods and New Tools in Mental Health Research (571) Mobile Health in Psychiatry (543) Depression and Mood Disorders; Suicide Prevention (1727) Applications of AI (312) Mental Health Issues in Adolescence (658)

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
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