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

Foundation Models and Their Applications in AI (43) Digital Mental Health Interventions, e-Mental Health and Cyberpsychology (1931) Foundations of AI (55) Applications of AI (208) Machine Learning (1868) Depression and Mood Disorders; Suicide Prevention (1581) Clinical Information and Decision Making (1752) Voice Phenotyping and Vocal Biomarkers (11)

Published on in Vol 4 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/69149, first published .
Digital Phenotyping for Detecting Depression Severity in a Large Payor-Provider System: Retrospective Study of Speech and Language Model Performance

Digital Phenotyping for Detecting Depression Severity in a Large Payor-Provider System: Retrospective Study of Speech and Language Model Performance

Digital Phenotyping for Detecting Depression Severity in a Large Payor-Provider System: Retrospective Study of Speech and Language Model Performance

Authors of this article:

Bradley Karlin1, 2 Author Orcid Image ;   Doug Henry1 Author Orcid Image ;   Ryan Anderson1 Author Orcid Image ;   Salvatore Cieri1 Author Orcid Image ;   Michael Aratow3 Author Orcid Image ;   Elizabeth Shriberg3 Author Orcid Image ;   Michelle Hoy3 Author Orcid Image
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