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All Journal Journal of Applied Engineering and Technological Science (JAETS)
Qaswaa Khaled Abood
Computer Science Department, College of Science, University of Baghdad
Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Industrial & Manufacturing Engineering

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Deep Learning and Its Role in Diagnosing Heart Diseases Based on Electrocardiography (ECG) Qaswaa Khaled Abood
Journal of Applied Engineering and Technological Science (JAETS) Vol. 5 No. 2 (2024): Journal of Applied Engineering and Technological Science (JAETS)
Publisher : Yayasan Riset dan Pengembangan Intelektual (YRPI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37385/jaets.v5i2.3746

Abstract

Diagnosing heart disease has become a very important topic for researchers specializing in artificial intelligence, because intelligence is involved in most diseases, especially after the Corona pandemic, which forced the world to turn to intelligence. Therefore, the basic idea in this research was to shed light on the diagnosis of heart diseases by relying on deep learning of a pre-trained model (Efficient b3) under the premise of using the electrical signals of the electrocardiogram and resample the signal in order to introduce it to the neural network with only trimming processing operations because it is an electrical signal whose parameters cannot be changed. The data set (China Physiological Signal Challenge -cspsc2018) was adopted, which is considered a challenge for researchers because it includes different age groups. Many diseases, and the results obtained by the system were 96% accurate.
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