Cost-Sensitive Learning for Anomaly Detection in Imbalanced ECG Data Using Convolutional Neural Networks

Cost-Sensitive Learning for Anomaly Detection in Imbalanced ECG Data Using Convolutional Neural Networks

Arrhythmia detection algorithms based on deep learning are attracting considerable interest due to their vital role in the diagnosis of cardiac abnormalities. Despite this interest, deep feature representation for ECG is still challenging and intriguing due to the inter-patient variability of the EC...

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Bibliographic Details
Main Authors: Muhammad Zubair, Changwoo Yoon
Format: Article
Language:English
Published: MDPI AG 2022-05-01
Series:Sensors
Subjects:
arrhythmia detection
ECG classification
cost-sensitive learning
imbalanced data
convolutional neural networks
Online Access:https://www.mdpi.com/1424-8220/22/11/4075

Internet

https://www.mdpi.com/1424-8220/22/11/4075

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