An Exploiting Machine Learning Technique for Predicting Disease - et. al., S.Usha, (Turkish Journal of Computer and Mathematics Education (TURCOMAT), 2021)
In the field of cardiology, coronary illness is assuming a crucial part since it is a significant reason for death everywhere on the world. In prior days ECG and PCG are utilized to avert and forecast coronary illness. It is exceptionally hard for some individuals to recognize the sickness on the grounds that the expense of the therapy is high. The doctor's job is to prognostic the coronary illness with the assistance of accessible information. The proposed works predict coronary illness by using Machine Learning Techniques. This technique helps doctors to prognostic coronary illness in the most straightforward way. In this work, the following classification algorithm Decision Tree, KNN, Logistic Regression, Naïve Bayes, Support Vector Machine of machine learning are used to predict heart disease. This methodology assists doctors with controlling the model which can improve the precision of prognostic. This model enhances the clinical data and oddity the best calculation by investigating its exactness result and furthermore creates generous mindfulness in the forecast of coronary illness.