An improved electrocardiogram arrhythmia classification performance with feature optimization
The proposed end-to-end architecture for ECG arrhythmia classification demonstrates simplicity in parameters and low complexity, making it highly effective for practical applications.
Authors
- Ade Iriani Sapitri (ORCID: https://orcid.org/0000-0003-4796-1901)
- Annisa Darmawahyuni (ORCID: https://orcid.org/0000-0002-0229-5717)
- Bambang Tutuko (ORCID: https://orcid.org/0000-0002-2051-8988)
- Muhammad Naufal Rachmatullah (ORCID: https://orcid.org/0000-0003-3553-3475)
- Anggun Islami (ORCID: https://orcid.org/0009-0001-3065-2873)
- Siti Nurmaini (ORCID: https://orcid.org/0000-0002-8024-2952)
- Jordan Marcelino (ORCID: https://orcid.org/0009-0002-2499-396X)
- Rendy Isdwanta (ORCID: https://orcid.org/0009-0009-2956-6175)
- Firdaus Firdaus
- Muhammad Ikhwan Perwira
Institutions
- Sriwijaya University (ID)
Publication Details
- Journal
- BMC Medical Informatics and Decision Making
- Published
- 2024-12-30
- DOI
- https://doi.org/10.1186/s12911-024-02822-7
- Citations
- 9
- Primary Topic
- ECG Monitoring and Analysis
- Type
- article
- Field-Weighted Citation Impact
- 3.62
Funders
- Universitas Sriwijaya