AI for Detecting and Predicting Postpartum Depression: Scoping Review
This scoping review analyzes 65 studies on AI in PPD, highlighting dominant use of classical machine learning, limited deep learning adoption, underuse of advanced preprocessing, inconsistent validation, and reliance on structured, unimodal data-mainly sociodemographic, clinical, and obstetric features.
Authors
- Ajisha Nayeem (ORCID: https://orcid.org/0000-0003-2407-6221)
- Javaid I. Sheikh (ORCID: https://orcid.org/0000-0002-5762-4186)
- Alaa Abd‐Alrazaq (ORCID: https://orcid.org/0000-0001-7695-4626)
- Mais Alkhateeb
- Arfan Ahmed
- Mohammed Alsahli
Institutions
- Saudi Electronic University (SA)
- Hamad bin Khalifa University (QA)
- Weill Cornell Medical College in Qatar (QA)
- Qatar University (QA)
Publication Details
- Journal
- Journal of Medical Internet Research
- Published
- 2026-01-08
- DOI
- https://doi.org/10.2196/77376
- Citations
- 1
- Primary Topic
- Maternal Mental Health During Pregnancy and Postpartum
- Type
- article
- Field-Weighted Citation Impact
- 41.85