Early identification of postpartum depression using machine learning-Reference-Cited by-同舟云学术

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Early identification of postpartum depression using machine learning

Published:2024-04-15 Issue:6 Volume:78 Page:372-373
ISSN:1323-1316
Container-title:Psychiatry and Clinical Neurosciences
language:en
Short-container-title:Psychiatry Clin Neurosci

Author:

Nakamura Yukako¹,Ueno Taro²,Takahashi Nagahide³^ORCID,Ichikawa Daisuke²,Yamauchi Aya⁴,Ozaki Norio¹³⁵^ORCID

Affiliation:

1. Department of Psychiatry Nagoya University Graduate School of Medicine Nagoya Japan

2. SUSMED, Inc. Tokyo Japan

3. Department of Child and Adolescent Psychiatry Nagoya University Graduate School of Medicine Nagoya Japan

4. Psychiatry/Child and Adolescent Psychiatry Nagoya University Hospital Nagoya Japan

5. Pathophysiology of Mental Disorders Nagoya University Graduate School of Medicine Nagoya Japan

Funder

Japan Agency for Medical Research and Development

Japan Society for the Promotion of Science

Publisher

Wiley

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/pcn.13659

Reference5 articles.

1. Perinatal mental illness: Definition, description and aetiology

2. Antenatal risk factors for postpartum depression: a synthesis of recent literature

3. Predicting women with depressive symptoms postpartum with machine learning methods

4. Development and validation of a machine learning‐based postpartum depression prediction model: A nationwide cohort study

5. Relation Between Perinatal Depressive Symptoms, Harm Avoidance, and a History of Major Depressive Disorder: A Cohort Study of Pregnant Women in Japan

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