A machine learning-based framework for analyzing mitral regurgitation-related signal patterns from photoplethysmography.

Bozkurt MR, Özen P.

DOI: 10.1515/bmt-2025-0417
Published: 2026-09-04
Container: Biomed Tech (Berl)
Publisher: Not recorded
Open access: no

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Cite this work

BibTeX

@article{allodium:10.1515/bmt-2025-0417,
  title = {A machine learning-based framework for analyzing mitral regurgitation-related signal patterns from photoplethysmography.},
  author = {Bozkurt MR and  Özen P.},
  year = {2026},
  journal = {Biomed Tech (Berl)},
  doi = {10.1515/bmt-2025-0417},
  url = {https://doi.org/10.1515/bmt-2025-0417}
}

RIS

TY  - JOUR
TI  - A machine learning-based framework for analyzing mitral regurgitation-related signal patterns from photoplethysmography.
AU  - Bozkurt MR
AU  -  Özen P.
PY  - 2026
JO  - Biomed Tech (Berl)
DO  - 10.1515/bmt-2025-0417
UR  - https://doi.org/10.1515/bmt-2025-0417
ER  -

APA

MR, B., & P., Ö. (2026). A machine learning-based framework for analyzing mitral regurgitation-related signal patterns from photoplethysmography.. Biomed Tech (Berl). https://doi.org/10.1515/bmt-2025-0417

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europe-pmc · retrieved 2026-09-25T04:10:35.089Z