Machine learning in the prediction of postpartum depression: A review-Reference-Cited by-同舟云学术

Machine learning in the prediction of postpartum depression: A review

Published:2022-07 Issue: Volume:309 Page:350-357
ISSN:0165-0327
Container-title:Journal of Affective Disorders
language:en
Short-container-title:Journal of Affective Disorders

Author:

Cellini Paolo,Pigoni Alessandro,Delvecchio Giuseppe,Moltrasio Chiara,Brambilla Paolo

Funder

Ministero della Salute

Publisher

Elsevier BV

Subject

Psychiatry and Mental health,Clinical Psychology

Reference49 articles.

1. Text mining applications in psychiatry: a systematic literature review;Abbe;Int. J. Methods Psychiatr. Res.,2016

2. The reliability of psychiatric diagnosis revisited: the clinician'’s guide to improve the reliability of psychiatric diagnosis;Aboraya;Psychiatry (Edgmont (Pa.: Township),2006

3. Depression levels in patients with hyperemesis gravidarum: a prospective case–control study;Aksoy;Springerplus,2015

4. Diagnostic and Statistical Manual of Mental Disorders;American Psychiatric Association,2013

5. Estimation of postpartum depression risk from electronic health records using machine learning;Amit;BMC Pregnancy Childbirth,2021

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