Heart Diseases Prediction using Deep Learning Neural Network Model
Sumit Sharma1, Mahesh Parmar2
1Sumit Sharma*, M.tech. Scholar, Dept. of CSE & IT, MITS Gwalior, Gwalior, Madhya Pradesh, India.
2Mahesh Parmar, Assistant Professor MITS, Dept. of CSE & IT, MITS Gwalior, Gwalior, Madhya Pradesh, India.
Manuscript received on December 15, 2019. | Revised Manuscript received on December 22, 2019. | Manuscript published on January 10, 2020. | PP: 2244-2248 | Volume-9 Issue-3, January 2020. | Retrieval Number: C9009019320/2020©BEIESP | DOI: 10.35940/ijitee.C9009.019320
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: 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.
Keywords: Deep Learning, Neural Network (NN), CNN, RNN, KNN, SVM, Heart Disease Dataset.
Scope of the Article: Deep Learning