Heart Disease Prediction using Machine Learning Techniques

Sharyu U. Kamble, Vaishnavi S. Jawanjal, Pooja P. Velapure, Priya K. Jadhav, Sanjivani S. Kadam

Abstract


Diseases related to Heart i.e. Cardiovascular Dis-eases (CVDs) are the main reason for the number of deaths in the course of the most recent couple of decades and has developed as the most perilous ailment, in India and in the entire world. In this way, there is a need for accurate, feasible and reliable system to analyze such maladies in time for legitimate treatment.

 Machine Learning algorithms and procedures have been im-plemented to various medical datasets to various medical datasets to investigate of extensive and complex information. Numerous analysts, as of late, have been using several methods to enable the health care industry and the professionals in the diagnosis of heart related diseases.

This paper demonstrates a survey of various models based on such algorithms and techniques and analyze their perfor-mance. Models depend on supervised learning algorithms such as Support Vector Machines (SVM), K-Nearest Neighbour (KNN), Naïve Bayes, Decision Trees (DT), Random Forest (RF) and ensemble models are discovered extremely prominent among the researchers.


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References


K. Sudhakar, Dr.M. Manimekalai “Study of Heart disease prediction using data mining” ISSN: 2277 128X

M. Revathi “Review of Heart Disease Prediction using Data mining techniques”

Sellappan Palaniappan, Rafiah Awang, "Intelligent Heart Disease Pre-diction System Using Data Mining Techniques", IJCSNS International Journal of Computer Science and Network Security, Vol.8 No.8, August 2008

Ankita Pimputkar, Jitendra S. Dhobi “A Survey on Heart Disease Predic-tion using Hybrid Technique in Data Mining” IJARIIE-ISSN(O)-2395-4396

Animesh Hazra, Subrata Kumar Mandal, Amit Gupta, Arkomita Mukher-jee and Asmita Mukherjee “Heart Diagnosis and prediction using machine learning and data mining : Review”

Burak Kolukisa , Hilal Hacilar, Gokhan Goy, Mustatfa Kus, Burcu Bakir-Gungor, Atilla Aral, Vehbi Cagrigungor “Evaluation of classification algorithms, Linear discriminate Analysis, and a New hybrid Feature selection methodology for the diagnosis of Coronary Artery Disease”

S. B. Patil and Y. S. Kumaraswamy, “Intelligent and effective heart attack prediction system using data mining and artificial neural network,” European Journal of Scientific Research, 2009, p. 642-656.

Quinlan, J.R, “Induction of decision trees”. Journal of Machine Learning, 1986, pp. 81-106.

Hanen Bouali and Jalel Akaichi et al. “Comparative study of Different classification techniques, heart Diseases uses Case.” 2014 13th Interna-tional Conference on Machine Learning and Applications

Cleveland database:http://archive.ics.uci.edu/ml/datasets/Heart+Disease

Statlog database e:http://archive.ics.uci.edu/ml/machine Learning databases/statlog/heart/

Aljaaf AJ, Al-Jumeily D, Hussain AJ, Dawson T, Fergus P, Al-Jumaily M. Predicting the likelihood of heart failure with a multi-level risk assess-ment using decision tree. Third international conference on technological advances in electrical, Beirut, Lebano

http://www.nhlbi.nih.gov/health/healthtopics/ topics/cad/

https://ieeexplore.ieee.org/document/8093512/

Heart Disease Prediction using machine learning techniques : A Survey: V,V Ramalingam, Ayantan Dandapath, M.Karthik Raja

Prediction of Heart Disease using data mining and machine learning algorithms and techniques , Nikhil Kumar Mutlaya, K.V.s. Kaushik DOI: 10.13140/RG.2.2.18185.75362


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