Open AccessHeart Diseases Prediction using Deep Learning Neural Network Model
Author(s) -
Sumit Sharma*,
Mahesh Parmar
Publication year - 2020
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.c9009.019320
Subject(s) - heart disease , random forest , artificial intelligence , machine learning , computer science , artificial neural network , naive bayes classifier , support vector machine , deep learning , field (mathematics) , bayes' theorem , disease , key (lock) , medicine , cardiology , mathematics , bayesian probability , computer security , pure mathematics
Deep learning plays an important role in the field of medical science in solving health issues and diagnosing various diseases. So in this paper, we will discuss heart disease. We proposed a model for heart disease prediction. Heart Disease is on of key area where Deep Neural Network can be used so we can improve the overall quality of the classification of heart disease. The classification can be performed on the various ways like KNN, SVM, Naïve Bayes, Random Forest. Heart Disease UCI dataset will be used to demonstrate Talos Hyper-parameter optimization is more efficient than others.