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

Reviews in Digital Mental Health (579) Digital Mental Health Interventions, e-Mental Health and Cyberpsychology (3375) Depression and Mood Disorders; Suicide Prevention (2527) Machine Learning (3353)

Published on in Vol 13 (2026)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/89352, first published .
Doctor explains brain scan results to patient on laptop.

Machine Learning for Comparative Antidepressant Selection in Major Depressive Disorder: Systematic Review

Machine Learning for Comparative Antidepressant Selection in Major Depressive Disorder: Systematic Review

Authors of this article:

Fiona He1 Author Orcid Image ;   Steven Huang2, 3 Author Orcid Image ;   Richard Wang4 Author Orcid Image ;   Aland Chang2 Author Orcid Image ;   Jennifer L Phillips5 Author Orcid Image ;   Christopher Sun3, 6 Author Orcid Image
Article Authors Cited by (2) Tweetations Metrics

Journals

  1. Baune B. Pharmaco-multiomics in major depressive disorder: a narrative review and proposed translational framework for difficult-to-treat and treatment-resistant depression. Frontiers in Pharmacology 2026;17 View
  2. Palka A, Kopyciński W, Krawczyk N, Wilczkowski P, Krzysztofek N, Kamela M, Boszczyk K, Grzybowska M, Baran A, Krawczyk O. ARTIFICIAL INTELLIGENCE IN PSYCHIATRIC DIAGNOSIS AND CLINICAL DECISION-MAKING: CURRENT EVIDENCE, CLINICAL APPLICATIONS, CHALLENGES AND FUTURE DIRECTIONS. International Journal of Innovative Technologies in Social Science 2026;5(3(51)) View