A Methodology For Early Prediction and Classification of Heart Diseases in Diabetic Patients With Machine Learning Techniques

Heart diseases severely affects how people live. A serious condition that affects people of all ages worldwide. Diabetes and heart disease patients have significantly higher mortality rates. A lot of lives may be saved if heart disease could be predicted earlier, especially in people who have diabetes. Advanced machine learning algorithms assist in providing an earlier prediction and accurate method for classifying and predicting cardiac disease. In order to predict cardiac disease, this paper presents a thorough overview of both traditional and modern machine learning algorithms. Furthermore, it suggests a cardiovascular disease prediction model that is both efficient and accurate, notably for diabetes patients. This approach suggested uses the support vector machines and random forests. The experiments were performed, and the findings demonstrate how effective the suggested framework.