Unveiling Irregular Heart Rhythms: Utilizing a Pretrained ResNet50 Convolutional Neural Network Autoencoder Strategy for Detecting Anomalies in ECG Signals

This study examines the application of ResNet50 (CNN) Autoencoders for identifying abnormalities in electrocardiogram (ECG) data using the PTB Diagnostic ECG Database. The dataset comprises 14,552 samples categorized as normal heartbeats and heartbeats affected by cardiac disorders. Utilizing Transp...

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Bibliographic Details

Published in:	2024 2nd World Conference on Communication & Computing (WCONF) pp. 1 - 4
Main Authors:	Agarwal, Muskan, Gill, Kanwarpartap Singh, Aggarwal, Priyanshi, Rawat, Ramesh Singh
Format:	Conference Proceeding
Language:	English
Published:	IEEE 12.07.2024
Subjects:	Anomaly detection Artificial Intelligence Autoencoder Convolution Convolutional neural networks Data models Decoding Deep Learning Electrocardiography Heart Heart beat Medical services Model Training Residual neural networks
Online Access:	Get full text
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