Quaternion-based recurrent neural networks and machine learning for 3D modeling of superficial femoral artery dynamics: a theoretical framework for enhanced treatment outcomes
- DOI
- 10.3389/fsurg.2026.1896488
- Published
- 2026-08-06
- Container
- Frontiers in Surgery
- Publisher
- Frontiers Media SA
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.3389/fsurg.2026.1896488,
title = {Quaternion-based recurrent neural networks and machine learning for 3D modeling of superficial femoral artery dynamics: a theoretical framework for enhanced treatment outcomes},
author = {Nikolaos D. Patelis and Eleni P. Georgiadi and Bahaa Arefai},
year = {2026},
journal = {Frontiers in Surgery},
doi = {10.3389/fsurg.2026.1896488},
url = {https://doi.org/10.3389/fsurg.2026.1896488}
}RIS
TY - JOUR TI - Quaternion-based recurrent neural networks and machine learning for 3D modeling of superficial femoral artery dynamics: a theoretical framework for enhanced treatment outcomes AU - Nikolaos D. Patelis AU - Eleni P. Georgiadi AU - Bahaa Arefai PY - 2026 JO - Frontiers in Surgery DO - 10.3389/fsurg.2026.1896488 UR - https://doi.org/10.3389/fsurg.2026.1896488 ER -
APA
Patelis, N. D., Georgiadi, E. P., & Arefai, B. (2026). Quaternion-based recurrent neural networks and machine learning for 3D modeling of superficial femoral artery dynamics: a theoretical framework for enhanced treatment outcomes. Frontiers in Surgery. https://doi.org/10.3389/fsurg.2026.1896488
Source records
- crossref · retrieved 2026-11-10T13:13:49.326Z