Voice analysis and deep learning for detecting mental disorders in pregnant women: a cross-sectional study

We developed a lightweight machine learning model to analyze pregnant women's voices for screening various mental disorders, achieving high sensitivity and demonstrating the potential of voice analysis as an effective and objective tool in perinatal mental health care.

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Publication Details

Journal
Discover Mental Health
Published
2025-02-08
DOI
https://doi.org/10.1007/s44192-025-00138-0
Citations
1
Primary Topic
Maternal Mental Health During Pregnancy and Postpartum
Type
article
Field-Weighted Citation Impact
1.88
Controls
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article

Voice analysis and deep learning for detecting mental disorders in pregnant women: a cross-sectional study

Hikaru Ooba, Hisashi Masuyama, Jota Maki
1 citations
Discover Mental Health
Maternal Mental Health During Pregnancy and Postpartum
1.88
article

Voice analysis and deep learning for detecting mental disorders in pregnant women: a cross-sectional study

Hikaru Ooba, Hisashi Masuyama, Jota Maki
article en
1 citations

Abstract

We developed a lightweight machine learning model to analyze pregnant women's voices for screening various mental disorders, achieving high sensitivity and demonstrating the potential of voice analysis as an effective and objective tool in perinatal mental health care.

Discover Mental HealthVol. 5(1)
Okayama University (JP)
Good health and well-being
Openalex Percentile: Top 19%
Maternal Mental Health During Pregnancy and Postpartum
1.88
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Voice analysis and deep learning for detecting mental disorders in pregnant women: a cross-sectional study — Hikaru Ooba, Hisashi Masuyama, et al. · Discover Mental Health (2025) | TGRS Research Map | TGRS