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

Artificial Intelligence (2129) Machine Learning (2076) New Methods (1134) Ubiquitous Health (uHealth) (134) Methods and New Tools in Mental Health Research (558) Digital Biomarkers and Digital Phenotyping (284) Computer-Aided Diagnosis (251) Diagnostic Tools in Mental Health (326)

Published on in Vol 26 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/58572, first published .
Automated Speech Analysis for Risk Detection of Depression, Anxiety, Insomnia, and Fatigue: Algorithm Development and Validation Study

Automated Speech Analysis for Risk Detection of Depression, Anxiety, Insomnia, and Fatigue: Algorithm Development and Validation Study

Automated Speech Analysis for Risk Detection of Depression, Anxiety, Insomnia, and Fatigue: Algorithm Development and Validation Study

Authors of this article:

Rachid Riad1 Author Orcid Image ;   Martin Denais1 Author Orcid Image ;   Marc de Gennes1 Author Orcid Image ;   Adrien Lesage1 Author Orcid Image ;   Vincent Oustric1 Author Orcid Image ;   Xuan Nga Cao1 Author Orcid Image ;   Stéphane Mouchabac2, 3 Author Orcid Image ;   Alexis Bourla2, 3, 4, 5 Author Orcid Image
Article Authors Cited by (3) Tweetations (3) Metrics

Journals

  1. Wang Q, Xu F, Wang X, Wu S, Ren L, Liu X. How Anxiety State Influences Speech Parameters: A Network Analysis Study from a Real Stressed Scenario. Brain Sciences 2025;15(3):262 View
  2. Dechant M, Lash E, Shokr S, O'Driscoll C. Future Me, a Prospection-Based Chatbot to Promote Mental Well-Being in Youth: Two Exploratory User Experience Studies. JMIR Formative Research 2025;9:e74411 View
  3. Yache V, Moradbakhti L, Neuner I, Veselinovic T. Predicting affective engagement and mental strain from prosodic speech features. Frontiers in Psychiatry 2025;16 View