The paper "Heart Disease Prediction Using Effective Machine Learning Techniques" by Dr. Bharani B R, Dr. Manjunatha S, Prof. Vijayalakshmi R Y, and Dr. Preethi S discusses the use of various machine learning algorithms and tools for predicting heart disease. The authors highlight the significant impact of heart disease, which claims approximately one life per minute globally, and emphasize the importance of early diagnosis and treatment. The paper reviews existing literature on heart disease prediction, including studies that have used decision trees, logistic regression, random forests, and other machine learning techniques. It also presents a proposed system for heart disease prediction, detailing the data preprocessing, model selection, and evaluation processes. The system aims to provide doctors with accurate and timely information to make informed decisions about patient care. The paper concludes by discussing the outputs of different machine learning algorithms and their potential in improving the accuracy of heart disease predictions.The paper "Heart Disease Prediction Using Effective Machine Learning Techniques" by Dr. Bharani B R, Dr. Manjunatha S, Prof. Vijayalakshmi R Y, and Dr. Preethi S discusses the use of various machine learning algorithms and tools for predicting heart disease. The authors highlight the significant impact of heart disease, which claims approximately one life per minute globally, and emphasize the importance of early diagnosis and treatment. The paper reviews existing literature on heart disease prediction, including studies that have used decision trees, logistic regression, random forests, and other machine learning techniques. It also presents a proposed system for heart disease prediction, detailing the data preprocessing, model selection, and evaluation processes. The system aims to provide doctors with accurate and timely information to make informed decisions about patient care. The paper concludes by discussing the outputs of different machine learning algorithms and their potential in improving the accuracy of heart disease predictions.