International Research Journal of Education and Technology

Heart failure is a critical medical condition that requires early detection to improve patient outcomes. This paper presents a machine learning-based heart failure prediction system that utilizes various classification algorithms to analyze patient data and predict the likelihood of heart failure. The study compares models such as Logistic Regression, Random Forest, Support Vector Machine (SVM), and Neural Networks. The results indicate that machine learning models significantly enhance predictive accuracy, aiding in timely medical interventions.

Keywords—Heart Failure, Machine Learning, Classification, Prediction, Medical Diagnosis.