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

Machine Learning (3128) Telehealth and Telemonitoring (3053) Natural Language Processing (1265) Depression and Mood Disorders; Suicide Prevention (2444) Bipolar Disorders (128) Voice Phenotyping and Vocal Biomarkers (32)

Published on in Vol 13 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/79093, first published .
Woman crying with a sound wave graphic, symbolizing emotional distress

Automated Speech Analysis for Screening and Monitoring Bipolar Depression: Machine Learning Model Development and Interpretation Study

Automated Speech Analysis for Screening and Monitoring Bipolar Depression: Machine Learning Model Development and Interpretation Study

Authors of this article:

Sooyeon Min1 Author Orcid Image ;   Tae-Sung Yeum2 Author Orcid Image ;   Daun Shin3 Author Orcid Image ;   Sang Jin Rhee1 Author Orcid Image ;   Hyunju Lee1 Author Orcid Image ;   Han-Sung Lee1 Author Orcid Image ;   Seongmin Park4 Author Orcid Image ;   Jihwa Lee4 Author Orcid Image ;   Yong Min Ahn1, 2 Author Orcid Image
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Journals

  1. Kobyakova О, Kanev A, Kurakova N, Karmina R. Artificial intelligence technologies in psychiatry: assessment of potential and barriers in the diagnosis of depressive states. A systematic review. Public Health 2026;6(2):24 View

Conference Proceedings

  1. Juthi S, Rahman M, Muni M, Billah M, Tasnim S, Ahmed K. 2026 IEEE 2nd International Conference on Quantum Photonics, Artificial Intelligence & Networking (QPAIN). AI-Driven Autoencoder–LightGBM Framework for Workplace Mental Health Screening View