• Kolli Punith Kumar
• Prof. Anoop Singh
• Dr. Varsha Namdeo

Heart disease is one of the most critical human diseases in the world and affects human life very badly. In heart disease, the heart is unable to push the required amount of blood to other parts of the body. Accurate and on time diagnosis of heart disease is important for heart failure prevention and treatment. Discovery of hidden patterns and relationships often goes unexploited. Advanced data mining techniques can help remedy this situation. Therefore classify the healthy people and people with heart disease, non-invasive-based methods such as machine learning are reliable and efficient. This paper studied a prototype Intelligent Heart Disease Prediction System (IHDPS) using data mining techniques, namely, Decision Trees, Naïve Bayes and Neural Network. Various results show that each technique has its unique strength to prediction parameters.

Heart Disease, Prediction, Data mining, Machine Learning, Decision Trees, Naïve Bayes

"Heart Disease Prediction using Machine Learning Techniques: A Review", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 7, page no.c444-c448, July-2021, Available :http://www.jetir.org/papers/JETIR2107326.pdf

"Heart Disease Prediction using Machine Learning Techniques: A Review", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 7, page no. ppc444-c448, July-2021, Available at : http://www.jetir.org/papers/JETIR2107326.pdf