Enhanced Model for Gestational Diabetes Mellitus Prediction Using a Fusion Technique of Multiple Algorithms with Explainability

Enhanced Model for Gestational Diabetes Mellitus Prediction Using a Fusion Technique of Multiple Algorithms with Explainability

Abstract High glucose levels during pregnancy cause Gestational Diabetes Mellitus (GDM). The risks include cesarean deliveries, long-term type 2 diabetes, fetal macrosomia, and infant respiratory distress syndrome. These risks highlight the need for accurate GDM prediction. This research proposes a...

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Bibliographic Details
Main Authors: Ahmad Hassan, Saima Gulzar Ahmad, Tassawar Iqbal, Ehsan Ullah Munir, Kashif Ayyub, Naeem Ramzan
Format: Article
Language:English
Published: Springer 2025-03-01
Series:International Journal of Computational Intelligence Systems
Subjects:
High glucose
Diabetes mellitus
Gestational diabetes prediction
Machine learning
Healthcare analytics
Predictive modelling
Online Access:https://doi.org/10.1007/s44196-025-00760-4
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