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Published in:

Volume 7 Issue 11
November-2020
eISSN: 2349-5162

Unique Identifier

JETIR2011019

Page Number

119-122

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Title

AN AUTOMATED DIAGNOSTIC SYSTEM FOR HEART DISEASE PREDICTION BASED ON CNN-LSTM

ISSN

2349-5162

Cite This Article

"AN AUTOMATED DIAGNOSTIC SYSTEM FOR HEART DISEASE PREDICTION BASED ON CNN-LSTM", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.7, Issue 11, page no.119-122, November-2020, Available :http://www.jetir.org/papers/JETIR2011019.pdf

Abstract

in this paper a heart disease prediction model for the prediction of occurrence of heart disease is presented. It aimed towards identifying the best classification algorithm for identifying the possibility of heart disease in a patient. This work is justified by performing a comparative study and analysis using three deep learning classification algorithms name CNN, DNN and LSTM are used at different levels of evaluations. This will provide researchers and medical practitioners to establish a better understanding and help them identify a solution to identify the best method for predicting the heart diseases. Results show that LSTM is better among three having accuracy of 95% in prediction of heart disease.

Key Words

LSTM, CNN, Prediction, Heart Disease, feature extraction

Cite This Article

"AN AUTOMATED DIAGNOSTIC SYSTEM FOR HEART DISEASE PREDICTION BASED ON CNN-LSTM", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.7, Issue 11, page no. pp119-122, November-2020, Available at : http://www.jetir.org/papers/JETIR2011019.pdf

Publication Details

Published Paper ID: JETIR2011019
Registration ID: 303171
Published In: Volume 7 | Issue 11 | Year November-2020
DOI (Digital Object Identifier):
Page No: 119-122
ISSN Number: 2349-5162

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Cite This Article

"AN AUTOMATED DIAGNOSTIC SYSTEM FOR HEART DISEASE PREDICTION BASED ON CNN-LSTM", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.7, Issue 11, page no. pp119-122, November-2020, Available at : http://www.jetir.org/papers/JETIR2011019.pdf




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