• Nisha M. Vadodariya

Heart disease remains one of the leading causes of mortality worldwide. Early and accurate prediction of heart disease can significantly improve patient outcomes. In this paper, we propose a novel approach using machine learning techniques to enhance the accuracy of heart disease prediction. The study compares various machine learning algorithms, including logistic regression, decision trees, random forests, and deep learning models, to determine the most effective method for early diagnosis. The proposed model is evaluated using publicly available datasets, and the results demonstrate improved performance in terms of accuracy, precision, and recall.

"A Novel Approach for Prediction of Heart Disease Using Machine Learning Techniques", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 3, page no.i687-i690, March-2025, Available :http://www.jetir.org/papers/JETIR2503893.pdf

"A Novel Approach for Prediction of Heart Disease Using Machine Learning Techniques", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 3, page no. ppi687-i690, March-2025, Available at : http://www.jetir.org/papers/JETIR2503893.pdf