Enhanced Machine Learning Technique for Predicting Cardiac Diseases Using ECG Data
Authors:-Priyanka Singh, Sameeksha Rahangdale, Virendra Kumar Tiwari, Gaurav Kishor Saxena
Abstract-Heart disease is a leading cause of morbidity and mortality worldwide. The advancement of machine learning (ML) has enabled the development of predictive models that can identify cardiac conditions with high accuracy. This paper presents an enhanced random forest-based ML technique for predicting cardiac diseases using ECG data. The proposed model evaluates several metrics including accuracy, classification error, F-measure, recall, and precision, achieving an accuracy rate of 92%. This technique transforms vast amounts of raw healthcare data into valuable insights for informed decision-making and forecasts in clinical settings. Our results demonstrate the efficacy of the proposed method in early diagnosis and prevention of heart diseases.
