MultiScaleFusion-Net and ResRNN-Net: Proposed Deep Learning Architectures for Accurate and Interpretable Pregnancy Risk Prediction

MultiScaleFusion-Net and ResRNN-Net: Proposed Deep Learning Architectures for Accurate and Interpretable Pregnancy Risk Prediction

Women exhibit marked physiological transformations in pregnancy, mandating regular and holistic assessment. Maternal and fetal vitality is governed by a spectrum of clinical, demographic, and lifestyle factors throughout this critical period. The existing maternal health monitoring techniques lack p...

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Bibliographic Details
Main Authors: Amna Asad, Madiha Sarwar, Muhammad Aslam, Edore Akpokodje, Syeda Fizzah Jilani
Format: Article
Language:English
Published: MDPI AG 2025-05-01
Series:Applied Sciences
Subjects:
maternal health prediction
deep learning in healthcare
pregnancy complication detection
explainable AI (XAI) in medicine
SHAP and GradCAM interpretability
imbalanced data handling
Online Access:https://www.mdpi.com/2076-3417/15/11/6152
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