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Prediction of Cardiovascular Disease Using Machine Learning Technique—A Modern Approach

Computers, Materials & Continua 2022年第4期71卷 855-869页

作者： visvasam devadoss ambeth kumar Chetan Swarup Indhumathi Murugan Abhishek kumar Kamred Udham Singh Teekam Singh Ramu Dubey Department of Computer Science&Engineering Panimalar Engineering CollegeAnna UniversityChennai600123India Department of Basic Science College of Science&Theoretical StudiesSaudi Electronic UniversityRiyadh-Male Campus 13316Saudi Arabia Department of Computer Science&IT JAIN(Deemed to be University)Bangalore560069India Department of Computer Science and Information Engineering National Cheng Kung UniversityTainan 701Taiwan Department of Mathematics Graphic Era Hill UniversityDehradun248002India Department of Mathematics J.C.Bose University of Science&TechnologyYMCAFaridabad121006India

Cardio Vascular disease(CVD),involving the heart and blood vessels is one of the most leading causes of death throughout the *** are several risk factors for causing heart diseases like sedentary lifestyle,unhealthy diet,obesity,diabetes,hypertension,smoking and consumption of alcohol,stress,hereditary factory *** cardiovascular disease and improving and treating the risk factors at an early stage are of paramount importance to save the precious life of a human *** present,the highly stressful life with bad lifestyle activities causes heart disease at a very young *** main aim of this research is to predict the premature heart disease based on machine learning *** paper deals with a novel approach using the machine learning algorithm for predicting the cardiovascular disease at the premature stage *** Vector Machine(SVM)is used for segregating the CVD patients based on their symptoms and medical *** experimentation results by using the proposed method will facilitate the medical practitioners to provide suitable treatment for the patients on time.A sophisticated model has been developed with the current approach to examine the various stages of CVD and the performance metrics used have given effective and fruitful results as compared to other machine learning techniques.

关键词： Machine learning support vector machine classification cardiovascular disease

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