Machine Learning Model for Heart Disease Prediction Using Tkinter for Graphic User Interface

Machine Learning Model for Heart Disease Prediction Using Tkinter for Graphic User Interface

Ms. Monika1, Ms. Shreya Sharma2, Mr. Aryan Suryavanshi3, Mr. Mohak Aggarwal4, Mr. Vinay Vashisth5

1 Assistant Professor 2,3,4,5 Student CSE Department

HMR Institute of Technology And Management, GGSIPU, Delhi 110036 shreyaaaa17@gmail.com

Abstract - One of the biggest causes of death in the globe is heart disease. Accurate cardiac disease prediction can aid in early detection and prevention. Heart disease has been accurately predicted using machine learning models. In this study, we investigated 6 machine learning modelsfor predicting heart disease [1]. To train and assess these models, we used the Cleveland HeartDisease dataset, a publically accessible dataset.
Age, sex, the type of chest discomfort, blood pressure, cholesterol levels, and other characteristics were among the features used to train the models. To determine the most reliable model for heart disease prediction, the outcomesfrom various models' tests were compared.

Keywords Decision Tree, SVM – support vector machine, Logistic Regression, Random Forest, HeartDisease Prediction, data preprocessing, feature extraction, Machine learning