International Journal of Electrical, Electronics and Data Communication (IJEEDC)
eISSN:2320-2084 , pISSN:2321-2950
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Volume-7,Issue-12  ( Dec, 2019 )
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Statistics report
Feb. 2020
Submitted Papers : 80
Accepted Papers : 10
Rejected Papers : 70
Acc. Perc : 12%
Issue Published : 84
Paper Published : 1397
No. of Authors : 3784
  Journal Paper

Paper Title
Applying Machine Learning Techniques for The Prediction of Heart Future Complications

Abstract
Heart performance problems are always detected after analyzing the heart electrocardiogram (ECG) signal. In case of abnormal measures of the heart performance are diagnosed from the analysis, a prediction of any future complications is always needed to help doctors to follow up the case. This paper describes the application of machine learning techniques for the prediction of heart future complications. Four techniques are explained and their results are compared. These are: the Linear Prediction Method (LPM), the Grid Partitioning, Fuzzy c-mean based on Neuro-Fuzzy prediction and also GMDH-PNN. Index terms - Electrocardiograph (ECG), Heart Diseases Diagnosis, Linear Prediction Method, Grid Partitioning Method, Fuzzy c-mean (FCM), Neuro-Fuzzy (ANFIS) , Polynomial Neural Network (PNN), GMDH.


Author - Kamel H. Rahouma, Rabab Hamed. M.Aly, Hesham F.A. Hamed, Mona A. Abo Eldahab

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| Published on 2019-04-12
   
   
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