Heart Attack Analysis and Prediction with Machine Learning Techniques

• DOI: 10.34110/forecasting.1489839
• Publication Date: 2024-07-06T15:21:23Z
• Authors: Shuaib Jasim; İbrahim Onaran; Mustafa Al-asadi
• Keywords: Word error rate

This study explores the use of machine learning algorithms to analyze and predict heart attacks, focusing on genetics, lifestyle, medical history, biometric factors. The data was analyzed using logistic regression, support vector machines, decision trees, random forests. Support machines were found be most effective model for predicting attack risk, with a high accuracy rate low error rate. highlights potential in assisting healthcare professionals individuals determining risk taking preventive measures.