Bridging accuracy and explainability in AI-ECG: A multi-stage hyperparameter tuning framework for reinforcement learning–based random forests
- DOI
- 10.1016/j.jelectrocard.2026.154453
- Published
- 2026-11
- Container
- Journal of Electrocardiology
- Publisher
- Elsevier BV
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1016/j.jelectrocard.2026.154453,
title = {Bridging accuracy and explainability in AI-ECG: A multi-stage hyperparameter tuning framework for reinforcement learning–based random forests},
author = {Karam Daoud and Rui Qi Ji and Nathan T. Riek and Murat Akcakaya and Ervin Sejdic and Tanmay Gokhale and Salah Al-Zaiti},
year = {2026},
journal = {Journal of Electrocardiology},
doi = {10.1016/j.jelectrocard.2026.154453},
url = {https://doi.org/10.1016/j.jelectrocard.2026.154453}
}RIS
TY - JOUR TI - Bridging accuracy and explainability in AI-ECG: A multi-stage hyperparameter tuning framework for reinforcement learning–based random forests AU - Karam Daoud AU - Rui Qi Ji AU - Nathan T. Riek AU - Murat Akcakaya AU - Ervin Sejdic AU - Tanmay Gokhale AU - Salah Al-Zaiti PY - 2026 JO - Journal of Electrocardiology DO - 10.1016/j.jelectrocard.2026.154453 UR - https://doi.org/10.1016/j.jelectrocard.2026.154453 ER -
APA
Daoud, K., Ji, R. Q., Riek, N. T., Akcakaya, M., Sejdic, E., Gokhale, T., & Al-Zaiti, S. (2026). Bridging accuracy and explainability in AI-ECG: A multi-stage hyperparameter tuning framework for reinforcement learning–based random forests. Journal of Electrocardiology. https://doi.org/10.1016/j.jelectrocard.2026.154453
Source records
- crossref · retrieved 2026-09-26T04:17:01.709Z