Robustness of Deep Learning models in electrocardiogram noise detection and classification-Reference-Cited by-同舟云学术

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Robustness of Deep Learning models in electrocardiogram noise detection and classification

Published:2024-08 Issue: Volume:253 Page:108249
ISSN:0169-2607
Container-title:Computer Methods and Programs in Biomedicine
language:en
Short-container-title:Computer Methods and Programs in Biomedicine

Author:

Rahman Saifur^ORCID,Pal Shantanu^ORCID,Yearwood John^ORCID,Karmakar Chandan^ORCID

Publisher

Elsevier BV

Reference35 articles.

1. Multi-lead model-based ECG signal denoising by guided filter;Hao;Eng. Appl. Artif. Intell.,2019

2. Contrastive blind denoising autoencoder for real time denoising of industrial IoT sensor data;Langarica;Eng. Appl. Artif. Intell.,2023

3. A meta-analysis on heart rate variability biofeedback and depressive symptoms;Pizzoli;Sci. Rep.,2021

4. Localization of myocardial infarction using a multi-branch weight sharing network based on 2-D vectorcardiogram;He;Eng. Appl. Artif. Intell.,2022

5. Electrocardiogram of a silver nanowire based dry electrode: Quantitative comparison with the standard Ag/AgCl gel electrode;Qin;IEEE Access,2019

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