iCOR: End-to-End Electrocardiography Morphology Classification Combining Multi-Layer Filter and BiLSTM

iCOR: End-to-End Electrocardiography Morphology Classification Combining Multi-Layer Filter and BiLSTM

Accurate delineation of ECG signals is critical for effective cardiovascular diagnosis and treatment. However, previous studies indicate that models developed for specific datasets and environments perform poorly when used with varying ECG signal morphology characteristics. This paper presents a nov...

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Bibliographic Details
Main Authors: Siti Nurmaini, Wisnu Jatmiko, Satria Mandala, Bambang Tutuko, Erwin Erwin, Alexander Edo Tondas, Annisa Darmawahyuni, Firdaus Firdaus, Muhammad Naufal Rachmatullah, Ade Iriani Sapitri, Anggun Islami, Akhiar Wista Arum, Muhammad Ikhwan Perwira
Format: Article
Language:English
Published: MDPI AG 2025-04-01
Series:Algorithms
Subjects:
deep learning
ECG signal delineation
multi-layer filter
noise removal
Online Access:https://www.mdpi.com/1999-4893/18/4/236
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