[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-123785-en":3,"doc-seo-123785-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},123785,3848291630094,"Emma Wilson","https://eur-avatar.wpscdn.com/davatar_085a072bc5b1113ac321206ff7593b45",8,"Research & Report","A Review on Prediction of Heart Disease based on Machine Learning and Datamining Techniques","Heart disease is a major global health risk and early identification is essential to enable timely, appropriate treatment. Cardiovascular conditions account for a substantial share of worldwide deaths, and the increasing burden over recent decades is linked to lifestyle change, inactivity, diet, obesity, stress, cholesterol, hypertension, and diabetes. This review summarizes existing machine learning and data mining approaches for heart disease classification and prediction, focusing on evaluating algorithm performance and identifying the most accurate and efficient diagnostic pathway.","A Review on Prediction of Heart Disease based on Machine Learning and Datamining Techniques  \nDurga Bhavani Adla1 Pachipala Yellamma2  \n1Research Scholar, Department ofCSE, Koneru Lakshmaiah Education Foundation, Green Fields, Vaddeswaram, Andhra  \nPradesh, India.  \n2 Associate Professor, Department ofCSE, Koneru Lakshmaiah Education Foundation, Green Fields, Vaddeswaram, Andhra  \nPradesh, India.  \nEmail: [durgabhavaniphd@gmail.com](durgabhavaniphd@gmail.com)  \nABSTRACT  \nHeart is the important organ in human body which supplies blood to all organs of the body. The abnormal situation of heart is considered as heart disease. According to WHO data cardiovascular, respiratory and neonatal conditions are the top three causes of Deaths in the World. In the year 2019 Heart diseases occupies 16%(9 million) of overall deaths happened in World. From two decades there is 4 times increase in the deaths with heart diseases this is because of change in life style, lack of physical activity, food habits, obesity ,stress, cholesterol ,high blood pressure and [diabetes.so](diabetes.so) there is a need to work on prediction of heart diseases to save many lives because prediction is the only way to prevent the disease. In this paper we will discuss about existing algorithms and existing work done in different machine learning and datamining techniques, which are concentrated more on the classification and prediction. main objective is to evaluate the performance of these algorithms and identify the most accurate and efficient approach for diagnosing heart diseases.  \nSome of the machine learning and data mining techniques are Artificial Neural Network(ANN),Decision Tree, Naive Bayes, SVM(Support Vector Machine),k-Nearest Neighbours (KNN),J48,SMO,Random forest and classification Tree.  \nKeywords-Machine learning; Prediction of Heart disease; Random Forest ;Decision Tree; Naive Bayes; SVM;  \n1.INTRODUCTION  \nHeart disease prediction grab the attention of many researchers in this decade because it is the main cause formost of the deaths around the world, so an early detection of the disease is needed. Some of the risk factors of heart diseases are changes in lifestyle, smoking and drinking habits, food habits, age, obesity, stress, cholesterol levels and high blood pressure.The diagnosis of heart disease is challenging and expensive task, if the heart condition of the person is known then only suitable treatment is provided, misdiagnosis leads to the death of the person. In the diagnosis of heart disease doctors first check for the signs and symptoms after that they will do physical examination of the person. Medical tests needed for heart disease treatment are like Blood test to know how much heart muscles are damaged, ECG to know the change in heartbeat, treadmill test to know how heart is working while doing some activity, echocardiogram to check heart valves and chambers problems, angiogram to know how much coronary arteries are blocked and MRI to know the structure of heart to identify the problems in detail [1] .  \nHeart diseases remain a major global health concern, and timely prediction and classification are vital for effective intervention and treatment. Machine learning techniques have shown great promise in analyzing large datasets and identifying patterns that can aid in the diagnosis and prognosis of heart diseases. In this study, we explore and  \ncompare various machine learning algorithms to determine their effectiveness in predicting and classifying heart diseases.  \nThe next sections of this paper consists of Literature Survey, Conclusion and Future Enhancement ,and References.  \n2. LITERATURE SURVEY  \nThere are many existing works related to disease prediction like brain tumor, diabetics and heart disease using machine learning and datamining techniques. some of the works which provided good accuracy and precision are discussed here.  \nAuthor in [2] M. J. A. Junaid et al, used hybrid techniques for prediction of heart disease wi","cbCaiuP9WsWB14ag","https://ap.wps.com/l/cbCaiuP9WsWB14ag","pdf",169491,1,6,"English","en",105,"# Abstract\n# Introduction\n# Literature Survey\n# Conclusion and Future Enhancement\n# References","[{\"question\":\"Why is predicting heart disease important?\",\"answer\":\"Heart disease is a leading cause of death worldwide, and early detection helps clinicians provide suitable treatment. Timely prediction supports effective intervention and reduces harm from misdiagnosis.\"},{\"question\":\"Which machine learning algorithms are discussed in this review?\",\"answer\":\"The document mentions Artificial Neural Network (ANN), Decision Tree, Naive Bayes, SVM, k-Nearest Neighbours (KNN), J48, SMO, Random Forest, and classification Tree, along with related hybrid models and deep learning approaches.\"},{\"question\":\"What data and evaluation focus does the review emphasize?\",\"answer\":\"The review concentrates on classification and prediction tasks, evaluating model accuracy and related performance measures. Several studies referenced use the Cleveland dataset from the UCI repository and compare results across algorithms.\"}]","A Review on Prediction of Heart Disease based on Machine Learning and Datamining Techniques | PDF",1785818552,15,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":28},"a-review-on-prediction-of-heart-disease-based-on-machine-learning-and-datamining-techniques","",{"@graph":36,"@context":85},[37,54,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/a-review-on-prediction-of-heart-disease-based-on-machine-learning-and-datamining-techniques/123785/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":62,"encodingFormat":61,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-04",true,{"@type":65,"interactionType":66,"userInteractionCount":4},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"Why is predicting heart disease important?","Question",{"text":75,"@type":76},"Heart disease is a leading cause of death worldwide, and early detection helps clinicians provide suitable treatment. Timely prediction supports effective intervention and reduces harm from misdiagnosis.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"Which machine learning algorithms are discussed in this review?",{"text":80,"@type":76},"The document mentions Artificial Neural Network (ANN), Decision Tree, Naive Bayes, SVM, k-Nearest Neighbours (KNN), J48, SMO, Random Forest, and classification Tree, along with related hybrid models and deep learning approaches.",{"name":82,"@type":73,"acceptedAnswer":83},"What data and evaluation focus does the review emphasize?",{"text":84,"@type":76},"The review concentrates on classification and prediction tasks, evaluating model accuracy and related performance measures. Several studies referenced use the Cleveland dataset from the UCI repository and compare results across algorithms.","https://schema.org",{"og:url":52,"og:type":87,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":89,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":92},[93,97,101,105,110,114,119,122,127,130,134],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":94,"show_sort_weight":95,"slug":96},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":98,"show_sort_weight":99,"slug":100},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":102,"show_sort_weight":103,"slug":104},"Exam",70,"exam",{"id":106,"doc_module":4,"doc_module_name":46,"category_name":107,"show_sort_weight":108,"slug":109},5,"Comic",60,"comic",{"id":21,"doc_module":4,"doc_module_name":46,"category_name":111,"show_sort_weight":112,"slug":113},"Technology",50,"technology",{"id":115,"doc_module":4,"doc_module_name":46,"category_name":116,"show_sort_weight":117,"slug":118},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":120,"slug":121},30,"research-report",{"id":123,"doc_module":4,"doc_module_name":46,"category_name":124,"show_sort_weight":125,"slug":126},9,"Religion & Spirituality",20,"religion-spirituality",{"id":125,"doc_module":4,"doc_module_name":46,"category_name":128,"show_sort_weight":125,"slug":129},"World Cup","world-cup",{"id":131,"doc_module":4,"doc_module_name":46,"category_name":132,"show_sort_weight":131,"slug":133},10,"Lifestyle","lifestyle",{"id":135,"doc_module":4,"doc_module_name":46,"category_name":136,"show_sort_weight":106,"slug":137},19,"General","general"]