• Rayakanti Rajani Nageshwar
• Dr. Sushopti D Gawade

Medical data is crucial to human existence as information technology advances. The medical database should contain both general and more detailed information about each patient to facilitate retrieval, analysis, diagnosis, and treatment of the patient's numerous illnesses and problems. The diagnosis of diabetes requires a complete medical assessment, medical history, and physical examination. The mortality rate can be minimized by early diabetes identification. The use of machine learning in the medical information system has been proven to be beneficial since it increases the number of successful treatments for diabetes mellitus while decreasing costs and improving diagnostic accuracy. For the automation of the overall process of diabetes prediction and severity estimation, a diabetic database is required. In this work diabetic prediction system is developed using classification models which includes namely Naïve Bayes, Logistic Regression, Support Vector Machine (SVM) and Adaboost.

"Prediction System for Type 2 Diabetics Using Machine Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 12, page no.b223-b230, December-2022, Available :http://www.jetir.org/papers/JETIR2212126.pdf

"Prediction System for Type 2 Diabetics Using Machine Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 12, page no. ppb223-b230, December-2022, Available at : http://www.jetir.org/papers/JETIR2212126.pdf