Machine learning prediction of human blood optical properties: a comparative study of optimized algorithms with SHAP-based interpretability analysis.

Omari F, Madani A, Kouider Amar M, Hentabli M, Tared S, Khaouane L, Laidi M, Benkortebi O, Zhang J

Open source

DOI
10.1080/10255842.2026.2723068
Published
2026 Aug 27
Container
Computer methods in biomechanics and biomedical engineering
Publisher
Not recorded
Open access
unknown

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BibTeX

@article{allodium:10.1080/10255842.2026.2723068,
  title = {Machine learning prediction of human blood optical properties: a comparative study of optimized algorithms with SHAP-based interpretability analysis.},
  author = {Omari F and Madani A and Kouider Amar M and Hentabli M and Tared S and Khaouane L and Laidi M and Benkortebi O and Zhang J},
  year = {2026},
  journal = {Computer methods in biomechanics and biomedical engineering},
  doi = {10.1080/10255842.2026.2723068},
  url = {https://doi.org/10.1080/10255842.2026.2723068}
}

RIS

TY  - JOUR
TI  - Machine learning prediction of human blood optical properties: a comparative study of optimized algorithms with SHAP-based interpretability analysis.
AU  - Omari F
AU  - Madani A
AU  - Kouider Amar M
AU  - Hentabli M
AU  - Tared S
AU  - Khaouane L
AU  - Laidi M
AU  - Benkortebi O
AU  - Zhang J
PY  - 2026
JO  - Computer methods in biomechanics and biomedical engineering
DO  - 10.1080/10255842.2026.2723068
UR  - https://doi.org/10.1080/10255842.2026.2723068
ER  - 

APA

F, O., A, M., M, K. A., M, H., S, T., L, K., M, L., O, B., & J, Z. (2026). Machine learning prediction of human blood optical properties: a comparative study of optimized algorithms with SHAP-based interpretability analysis.. Computer methods in biomechanics and biomedical engineering. https://doi.org/10.1080/10255842.2026.2723068

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