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

Non-randomized Protocols and Methods (ehealth) (745) Mobile Health (mhealth) (3741) mHealth for Data Collection and Research (1288) Substance Abuse (571) Wearable Devices and Sensors (1245) Machine Learning (2306) Digital Biomarkers and Digital Phenotyping (340) Ecological Momentary Assessment (EMA) (446)

Published on in Vol 14 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/71374, first published .
Smartwatch displaying fitness data: heart rate, steps, and calories burned.

Development of a Cohesive Predictive Model for Substance Use Disorder Rehabilitation Using Passive Digital Biomarkers, Psychological Assessments, and Automated Facial Emotion Recognition: Protocol for a Prospective Cohort Study

Development of a Cohesive Predictive Model for Substance Use Disorder Rehabilitation Using Passive Digital Biomarkers, Psychological Assessments, and Automated Facial Emotion Recognition: Protocol for a Prospective Cohort Study

Authors of this article:

Andrea P Garzón-Partida1, 2 Author Orcid Image ;   Kimberly Magaña-Plascencia1, 2 Author Orcid Image ;   Diana Emilia Martínez-Fernández3 Author Orcid Image ;   Joaquín García-Estrada1, 2 Author Orcid Image ;   Sonia Luquin1, 2 Author Orcid Image ;   David Fernández-Quezada1, 2 Author Orcid Image
Article Authors Cited by (2) Tweetations Metrics

Journals

  1. Morales A, Reis T, Panisson A, Ourique F, Sene I. Affective Intelligent Systems in Healthcare: A Systematic Review. Technologies 2026;14(3):188 View
  2. García-Estrada J, Martínez-Fernández D, Pérez-Alcaraz I, Mondragón-Gomar C, Aguilar-García I, Luquin S, Fernández-Quezada D. Automated Facial Emotion Recognition System Detects Altered Emotional Processing During Craving Induction in Individuals with Substance Use Disorder. Healthcare 2026;14(10):1422 View