A Comprehensive Study on Postpartum Depression Prediction using Machine Learning Approaches

Deepthi Rani S S; Lekshmi M S

doi:10.36948/ijfmr.2025.v07i03.45181

A Comprehensive Study on Postpartum Depression Prediction using Machine Learning Approaches

Author(s)	Ms. Deepthi Rani S S, Lekshmi M S
Country	India
Abstract	Postpartum depression (PPD) remains a pervasive mental health challenge affecting new mothers worldwide. With prevalence rates rising and the multifaceted etiology of PPD complicating early diagnosis, traditional screening tools—while useful—often fall short in capturing the broad spectrum of social, behavioral, and clinical risk factors. This literature review examines the evolution of computational methodologies employed to predict PPD, with particular emphasis on machine learning (ML) approaches, IoT-based monitoring, social media analytics, and neuro-fuzzy models. We analyze studies that range from personalized maternal sleep quality assessments using IoT devices to advanced deep neural network models for risk classification. In comparing these techniques, we discuss their predictive accuracies, advantages, limitations, and the inherent trade-offs between continuous monitoring, real-time insights, and computational complexity. Our synthesis reveals that while ML-based risk prediction models tend to provide high accuracy, challenges remain in data integration, model interpretability, and the generalizability of results across diverse populations. Finally, we outline the key areas for future research, including the development of robust, real-time screening systems that integrate multiple data sources and the need for culturally adapted models.
Keywords	Postpartum depression, machine learning, IoT, social media analytics, neuro-fuzzy models, real-time screening, risk prediction.
Field	Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In	Volume 7, Issue 3, May-June 2025
Published On	2025-05-21
DOI	https://doi.org/10.36948/ijfmr.2025.v07i03.45181
Short DOI	https://doi.org/g9mh6t

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A Comprehensive Study on Postpartum Depression Prediction using Machine Learning Approaches

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