Feedback Mechanism in Heart Disease Classification

Heart diseases are becoming more common every day, making it important and concerning to predict and diagnose these conditions accurately and efficiently. This research paper focuses on identifying patients who are more likely to have a heart disease based on various medical attributes and also examines which attributes are contributing to the heart disease. To address this issue, we developed a heart disease prediction system that uses machine learning algorithms, such as logistic regression, to predict and classify patients with heart disease. This system helps to relieve a significant amount of pressure on medical professionals by accurately identifying the likelihood of a patient having a heart disease. In addition, the heart disease prediction system improves medical care and reduces costs. Overall, this project provides valuable knowledge that can aid in the prediction of heart disease in patients and is implemented in .pynb format.