• Maheshwari

Cardiovascular diseases, especially heart attacks, are a major global cause of death. Early risk detection can improve outcomes significantly. This project uses machine learning (ML) to develop a predictive model for heart attack risk, trained on medical data including age, cholesterol, blood pressure, and other biomarkers. Algorithms like logistic regression, decision trees, and neural networks were tested, with the best- performing model offering high accuracy. The system aims to support healthcare professionals in identifying high-risk individuals for early intervention.

Heart Attack Detector Using Machine Learning

"Heart Attack Detector Using Machine Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 5, page no.322-326, May-2025, Available :http://www.jetir.org/papers/JETIRGV06047.pdf

"Heart Attack Detector Using Machine Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 5, page no. pp322-326, May-2025, Available at : http://www.jetir.org/papers/JETIRGV06047.pdf