Pediatric diabetes prediction using machine learning.

ABSTRACT: Diabetes is a chronic condition that affects a substantial portion of the global population and is linked to elevated mortality rates and a range of severe health complications. Despite its clinical importance, progress in diabetes research is often constrained by the limited availability of comprehensive datasets and robust predictive models. To address these challenges, researchers are increasingly turning to big data analytics and machine learning (ML) methodologies. This study presents the development of an ML-based system aimed at predicting the likelihood of diabetes and classifying its various types. A novel dataset, termed Diabetes Types Dataset, was constructed by integrating four heterogeneous dataset sources: paediatrics data from the Mansoura University Children Hospital reposi

SUBMITTER: El-Sayyid El-Bashbishy A 

PROVIDER: S-EPMC12808089 | biostudies-literature | 2026 Jan

REPOSITORIES: biostudies-literature