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Optimizing Machine Learning for Diabetes Detection: Addressing Class Imbalance with SMOTE and Random Forest Ensemble Learning

2025-02-25

Abstract excerpt

Diabetes is a widespread metabolic disorder with serious health consequences including cardiovascular disease, kidney failure, and neuropathy. An early and precise diagnosis is crucial for effective disease management. However, conventional diagnostic methods, such as fasting blood glucose (FBG) and oral glucose tolerance tests (OGTT), are resource-intensive and impractical for large-scale screening, particularly...

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Literature Corpus work: 2a439106-733f-5e84-944a-de51063114a8
DOI: 10.22541/au.174048501.13296000/v1

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