Published on in Vol 13 (2025)
Preprints (earlier versions) of this paper are
available at
https://preprints.jmir.org/preprint/58649, first published
.

Journals
- Xie K, Jiang S, Wang Y, Chen H, Wu X, Xu B. Association of immune-inflammatory biomarkers during pregnancy and the postpartum period with postpartum depression symptoms: A cross-sectional and longitudinal retrospective analysis. Brain, Behavior, and Immunity 2025;129:42 View
- Li Y, Xiao M, Li Y, Lv L, Zhang S, Liu Y, Zhang J. Machine Learning for the Prediction of Acute Kidney Injury in Critically Ill Patients With Coronary Heart Disease: Algorithm Development and Validation. JMIR Medical Informatics 2025;13:e72349 View
- García-Méndez S, de Arriba-Pérez F. Detecting and Explaining Postpartum Depression in Real-Time with Generative Artificial Intelligence. Applied Artificial Intelligence 2025;39(1) View
- Xia J, Chen C, Lu X, Zhang T, Wang T, Wang Q, Zhou Q. Artificial intelligence-oriented predictive model for the risk of postpartum depression: a systematic review. Frontiers in Public Health 2025;13 View
Conference Proceedings
- Mathew J, Ramasamy G. 2025 International Conference on Emerging Technologies in Computing and Communication (ETCC). Graph Convolutional Networks for Predicting Postpartum Depression: A Symptom-Based Analysis View