ABSTRACT

This research presents a fresh method for forecasting Gestational Diabetes Mellitus (GDM) via a Genetic Algorithm Enhanced Artificial Neural Network (ANN) model. By utilizing genetic algorithms, the ANN's predictive potential is enhanced, providing a novel approach for early GDM detection and intervention. The study details the fusion of genetic algorithms with ANN and showcases its success on a gestational diabetes related Kaggle dataset, achieving an accuracy of 98.34% that surpasses other machine learning and deep learning models Keywords: Gestational Diabetes Mellitus, Genetic Algorithm, ANN
Publication date: 15/10/2023

https://ijbpas.com/pdf/2023/October/MS_IJBPAS_2023_OCTOBER_SPCL_1020.pdf

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https://doi.org/10.31032/IJBPAS/2023/12.10.1020