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DAE-ConvBiLSTM: End-to-end learning single-lead electrocardiogram signal for heart abnormalities detection
- Bambang Tutuko,
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Annisa Darmawahyuni ,
Roles Conceptualization, Formal analysis, Methodology, Writing – original draft
* E-mail: sitinurmaini@gmail.com, siti_nurmaini@unsri.ac.id (SN); riset.annisadarmawahyuni@gmail.com, annisadarmawahyuni@unsri.ac.id (AD)
Affiliation Intelligent System Research Group, Faculty of Computer Science, Universitas Sriwijaya, Palembang, Indonesia
⨯ -
Siti Nurmaini ,
Roles Formal analysis, Funding acquisition, Methodology
* E-mail: sitinurmaini@gmail.com, siti_nurmaini@unsri.ac.id (SN); riset.annisadarmawahyuni@gmail.com, annisadarmawahyuni@unsri.ac.id (AD)
Affiliation Intelligent System Research Group, Faculty of Computer Science, Universitas Sriwijaya, Palembang, Indonesia
⨯ -
Alexander Edo Tondas,
Roles Validation
Affiliation Department of Cardiology & Vascular Medicine, Dr. Mohammad Hoesin Hospital, Palembang, Indonesia
⨯ - Muhammad Naufal Rachmatullah,
- Samuel Benedict Putra Teguh,
- Firdaus Firdaus,
- Ade Iriani Sapitri,
- Rossi Passarella
https://orcid.org/0000-0002-0229-5717
DAE-ConvBiLSTM: End-to-end learning single-lead electrocardiogram signal for heart abnormalities detection
- Bambang Tutuko,
- Annisa Darmawahyuni,
- Siti Nurmaini,
- Alexander Edo Tondas,
- Muhammad Naufal Rachmatullah,
- Samuel Benedict Putra Teguh,
- Firdaus Firdaus,
- Ade Iriani Sapitri,
- Rossi Passarella
- Published: December 30, 2022
- https://doi.org/10.1371/journal.pone.0277932