Open AccessHEART DISEASE PREDICTION USING MACHINE LEARNING TECHNIQUES
Author(s) -
Anurag Yadav
Publication year - 2021
Publication title -
information technology in industry/information technology in industry
Language(s) - English
Resource type - Journals
eISSN - 2204-0595
pISSN - 2203-1731
DOI - 10.17762/itii.v9i1.120
Subject(s) - machine learning , support vector machine , decision tree , artificial intelligence , random forest , computer science , naive bayes classifier , heart disease , disease , automation , medical diagnosis , medicine , engineering , mechanical engineering , pathology , cardiology
In few previous decades around the globe the reason for extensive number of deaths is cardiovascular disease or Heart related disease and not only in India but all around the world has emerged as a life-threatening disease. So for the correct treatment and in time diagnosis for this disease the need of feasible, accurate and reliable system is encountered. For automation of analysis of the sophisticated and huge data, to the various medical dataset of Machine Learning techniques and methods are applied. In recent times many researchers for the health care industry assistance with the help of various techniques of Machine Learning, this in turn helps the professionals in the procedure of the heart related disease diagnosis. A survey of various models that accepts such techniques and algorithms and their performance analysis is presented in this paper. Within the researchers few very fashionable Model supported supervised learning algorithms are Random forest (RF), Decision Tree (DT), Naïve Bayes, ensemble models, K-Nearest Neighbour (KNN) and Support Vector Machine (SVM).