• Kaluputi Anitha
• E.Ramesh Reddy

Diabetes is a chronic metabolic disorder characterized by elevated blood sugar levels, posing significant health risks if left unmanaged. Early detection and intervention are crucial for effective disease management and prevention of complications. In recent years, machine learning (ML) techniques have shown promise in predicting diabetes onset, aiding in proactive healthcare measures. This study presents a comprehensive review of ML methodologies applied to predict diabetes, encompassing various data sources including clinical, genetic, and lifestyle factors. Leveraging datasets from diverse populations, this research investigates the efficacy of ML algorithms in accurately identifying individuals at risk of developing diabetes.

Diabetes, Machine Learning, Prediction, Support vector Machine.

"PREDICTION OF DIABETES USING ML TECHNIQUES", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 6, page no.536-539, June-2024, Available :http://www.jetir.org/papers/JETIRGL06088.pdf

"PREDICTION OF DIABETES USING ML TECHNIQUES", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 6, page no. pp536-539, June-2024, Available at : http://www.jetir.org/papers/JETIRGL06088.pdf