• Hamza Girach
• Mohd Zaid Gandhi
• Adnan Hathiyari
• Shiburaj Pappu
• Mohammed Juned

Heart disease is considered one of the leading causes of death worldwide. Prediction is a difficult task that requires specialized and advanced knowledge and cannot be easily predicted by a doctor. Healthcare is still "rich in information" but "poor in knowledge". Within the medical system, a lot of data is available on the Internet. However, there is a lack of effective analytical tools to reveal hidden relationships and patterns in the data. Medical diagnostic automation systems increase medical efficiency and reduce costs. This web application aims to predict the outbreak of illness based on data obtained from medical research conducted by the Kaggle and Cleveland Foundation, especially in the field of heart disease. The purpose is to extract hidden patterns by applying data mining techniques to datasets. It is noteworthy for heart disease and predicts the presence of heart disease in patients whose presence is assessed on a scale. Predicting heart disease requires large amounts of data that are too complex to process and analyze using traditional techniques.

Prediction, heart disease, machine learning, algorithms, analysis.

"Heart Disease Prediction using Machine Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 4, page no.f529-f533, April-2022, Available :http://www.jetir.org/papers/JETIR2204566.pdf

"Heart Disease Prediction using Machine Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 4, page no. ppf529-f533, April-2022, Available at : http://www.jetir.org/papers/JETIR2204566.pdf