An improved electrocardiogram arrhythmia classification performance with feature optimization

An improved electrocardiogram arrhythmia classification performance with feature optimization

Abstract Background Automatic classification of arrhythmias based on electrocardiography (ECG) data faces several significant challenges, particularly due to the substantial volume of clinical data involved in ECG signal analysis. The volume of clinical data has increased considerably, especially wi...

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Main Authors: Annisa Darmawahyuni, Siti Nurmaini, Bambang Tutuko, Muhammad Naufal Rachmatullah, Firdaus Firdaus, Ade Iriani Sapitri, Anggun Islami, Jordan Marcelino, Rendy Isdwanta, Muhammad Ikhwan Perwira
Format: Article
Language:English
Published: BMC 2024-12-01
Series:BMC Medical Informatics and Decision Making
Subjects:
Arrhythmia
Electrocardiogram signals
Feature extraction
Feature selection
Machine learning
Online Access:https://doi.org/10.1186/s12911-024-02822-7
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https://doi.org/10.1186/s12911-024-02822-7

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