Heart Disease Prediction System using Machine Learning
Abdul Majeed K M, Athithi Ajay, Ayshath Safana, Rabiyath Muneefa, Sakshi S Gowda
Abstract
The "heart disease prediction system using machine learning" project. Huge amounts of medical insurance data are collected in the medical industry, but they are not quarried and analysed properly to uncover secret knowledge, act decisively, or discover the relationships that link up styles. The goal of this research is to develop an effective decision support system for the . The likelihood of the patient developing a cardiac illness can be predicted using the patient's medical profile (age, gender, blood pressure, blood sugar, cholesterol, chest discomfort, ecg graph, etc.). There are five possible levels of likelihood (class label): not at all, low, medium, high, and very high. The system will forecast the class label if an unknown sample is present.