Smote-Based Heart Disease Detection Utilizing AI and Ml Stacking Classifiers

One of the most common illnesses today is heart disease, therefore it's essential for those who work in health care to work with their patients to find ways to protect their health and prolong their lives. In this study, the performance of various classifiers was examined in order to correctly identify the guts disease dataset and/or predict the cases of art condition using minimal criteria. Healthcare professionals have accumulated a lot of knowledge, including some private data. Taking wise decisions is made easier by this data collection. In this scenario, a Heart Disease Prediction System (HDPS) is built to predict the risk level of gastroenteritis by applying K-Nearest Neighbor, Logistic Regression, Decision Tree, Support Vector Machine, and Random Forest Classifier methods.