Integration of Machine Learning Techniques in ECG-Based Multiclass Arrhythmia Classification with Explainability Analysis
- DOI
- 10.3390/bios16060326
- Published
- 2026-06-03
- Container
- Biosensors
- Publisher
- MDPI AG
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.3390/bios16060326,
title = {Integration of Machine Learning Techniques in ECG-Based Multiclass Arrhythmia Classification with Explainability Analysis},
author = {Abdullah and Zulaikha Fatima and Abdollah Abadian and Carlos Guzmán Sánchez Mejorada and Miguel Jesús Torres Ruiz and Rolando Quintero Téllez},
year = {2026},
journal = {Biosensors},
doi = {10.3390/bios16060326},
url = {https://doi.org/10.3390/bios16060326}
}RIS
TY - JOUR TI - Integration of Machine Learning Techniques in ECG-Based Multiclass Arrhythmia Classification with Explainability Analysis AU - Abdullah AU - Zulaikha Fatima AU - Abdollah Abadian AU - Carlos Guzmán Sánchez Mejorada AU - Miguel Jesús Torres Ruiz AU - Rolando Quintero Téllez PY - 2026 JO - Biosensors DO - 10.3390/bios16060326 UR - https://doi.org/10.3390/bios16060326 ER -
APA
Abdullah, Fatima, Z., Abadian, A., Mejorada, C. G. S., Ruiz, M. J. T., & Téllez, R. Q. (2026). Integration of Machine Learning Techniques in ECG-Based Multiclass Arrhythmia Classification with Explainability Analysis. Biosensors. https://doi.org/10.3390/bios16060326
Source records
- crossref · retrieved 2026-09-26T12:47:52.988Z