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© 2019, IJCSE All Rights Reserved 109 International Journal of Computer Sciences and Engineering Open Access Review Paper Vol.-7, Issue-7, July 2019 E-ISSN: 2347-2693 A Review on Intutive Prediction of Heart Disease Using Data Mining Techniques Akansha Jain 1* , Manish Ahirwar 2 , Rajeev Pandey 3 1,2,3 Department of Computer Science, Rajiv Gandhi Proudyogiki Vishwavidyalaya, Bhopal, India * Corresponding Author: [email protected],, Tel.: +91-7879780944 DOI: | Available online at: Accepted: 16/Jul/2019, Published: 31/Jul/2019 Abstract Healthcare evaluates clinical datasets regularly by specialist's learning and action. In the clinical field, computer- supported with prediction system is used in the healthcare department. Data mining approach provides innovation and strategy to replace voluminous information into useful data for achieving a decision. By utilizing information mining systems it needs less investment for the forecast of the sickness with more accuracy and precision. This paper evaluates various classifiers and algorithms are used for the expectation of cardiovascular illness. Keywords WEKA tool, Data Mining techniques, Heart disease prediction, Computer Aided Support System. I. INTRODUCTION Most fundamental hard-working muscular organ of our body is heart. In circulatory system, blood is transferred through the veins in heart. This muscular system plays a vital role as it transports oxygen, blood and other materials to the various body parts [1]. It might cause serious wellbeing conditions including death if the heart does not work appropriately. It results in several illness, disability and death. Modifiable hazard factors incorporate weight, smoking, absence of physical movement, etc. Illness diagnosis plays a leading role in clinical field. Intelligent data mining algorithms tackle problem of clinical dataset prediction involving several inputs. Decision support systems with computer-based information and can assist in accomplishing health related tests at a decreased expense. Computerized system needs a relative study of different techniques available for exact and efficient execution. This paper predicts numerous coronary illness prediction by utilizing the approaches of data mining proposed in recent years. Section I contains the introduction of data mining algorithms, data mining tools and cardiovascular diseases, Section II contains the related work of prediction system using different datasets using different approaches, Section III contains the conclusion. A. DATA MINING ALGORITHMS Various algorithms formulates due to different research works on data mining. These techniques are straightforwardly utilized for developing frameworks or to find crucial inferences and conclusions from the resulted dataset. Various well-known techniques are Support vector machine, K-means, Naïve Bayes, Artificial neural network etc are discussed.
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