Diabetes Prediction Using Machine Learning Techniques

Diabetes Prediction Using Machine Learning Techniques

Dr. Mahesh Kotha, Aluri Gopi

Associate professor, Department of CSE (AI&ML), CMR Technical Campus, Hyderabad.

Associate Professor, Department of Electronics and Communication Engineering, CMR Engineering College, Hyderabad.

Abstract: Diabetes is one of the most prevalent chronic diseases, affecting millions globally. Early detection and prediction of diabetes can lead to timely intervention and better disease management. In recent years, machine learning algorithms, particularly Support Vector Machines (SVM), have been widely applied to predict diabetes with high accuracy. This paper explores the application of SVM for diabetes prediction, focusing on its methodology, performance, and effectiveness in classifying diabetic and non-diabetic patients using clinical data. The study also highlights the advantages, challenges, and potential improvements for SVM in this medical domain.

Keywords: Diabetes, Support Vector Machines (SVM), Machine Learning, Prediction, Classification, Clinical Data.