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

Formative Evaluation of Digital Health Interventions (3411) Artificial Intelligence (2315) Decision Support for Health Professionals (1624) Diagnostic Tools in Mental Health (337) Machine Learning (2212) Computer-Aided Diagnosis (277) Depression and Mood Disorders; Suicide Prevention (1749) Development and Evaluation of Research Methods, Instruments and Tools (792) mHealth for Screening (306)

Published on in Vol 9 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/56057, first published .
Comparative Efficacy of MultiModal AI Methods in Screening for Major Depressive Disorder: Machine Learning Model Development Predictive Pilot Study

Comparative Efficacy of MultiModal AI Methods in Screening for Major Depressive Disorder: Machine Learning Model Development Predictive Pilot Study

Comparative Efficacy of MultiModal AI Methods in Screening for Major Depressive Disorder: Machine Learning Model Development Predictive Pilot Study

Authors of this article:

Donghao Chen1 Author Orcid Image ;   Pengfei Wang2, 3 Author Orcid Image ;   Xiaolong Zhang2, 3 Author Orcid Image ;   Runqi Qiao1 Author Orcid Image ;   Nanxi Li2, 3 Author Orcid Image ;   Xiaodong Zhang2, 3 Author Orcid Image ;   Honggang Zhang1 Author Orcid Image ;   Gang Wang2, 3 Author Orcid Image
Article Authors Cited by (4) Tweetations Metrics

Journals

  1. Wang L, Wang C, Li C, Murai T, Bai Y, Song Z, Zhang S, Zhang Q, Huang Y, Bi X, Jiang J. AI-assisted multi-modal information for the screening of depression: a systematic review and meta-analysis. npj Digital Medicine 2025;8(1) View
  2. Feng L, Li N, Jilka S, Firth J, Wang G. Understanding mood through facial expressions: opportunities and challenges in depression detection. Science Bulletin 2025;70(22):3687 View
  3. Li H, Li S. Computer‐Assisted Performance‐Based Assessment for Mental Health: A Scoping Review. PsyCh Journal 2026;15(2) View

Conference Proceedings

  1. Anuj M, Nancy R G. 2025 9th International Conference on Electronics, Communication and Aerospace Technology (ICECA). A Multi-Modal AI Framework for Real-Time Depression and Anxiety Detection using Voice, Text, and Facial Cues View