Classification of Some Heart Diseases Using Machine Learning Algorithms

Abstract

Heart illness is one of the most widely common sicknesses overall and is the primary wellspring of death; various sorts of coronary illness can be distinguished through numerous clinical trials; with the gigantic improvement in computer programming, particularly in the field of illness characterization, there are different AI calculations used to direct examinations and analyses, By accurately and quickly classifying disorders, these technologies can significantly benefit the medical industry and save time for both patients and physicians. The study aims to employ machine learning algorithms in classifying heart diseases, which helps patients know the health problems they suffer from and also contributes to helping medical staff classify these diseases and choose the best algorithm to classify some heart diseases in the early stages by comparing the evaluation criteria for these algorithms, The dataset utilized in this examination contains 24 features, one objective variable, and 663 instances of 522 cardiovascular sicknesses for four classes got from the drums of patients confessed to Ibn Al-Baytar Particular Place for Heart Medical procedure, which is (coronary artery insufficiency, AlKadhimiya Educating Clinic's 141 wellness cases (heart valve, heart failure, congenital abnormality). In this examination, AI calculations were utilized, in particular, the DT algorithm addressed by the (C4.5) algorithm and the NB algorithm; The outcomes showed that the (C4.5) DT algorithm has unrivalled execution in grouping a few cardiovascular sicknesses with a precision of 93.23 % contrasted with another classification algorithm.

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