An interpretable machine learning framework using multi-phase computed tomography for differentiation of adrenal lipid-poor adenomas and pheochromocytomas.

Zhao P, Zhu F, Yan C, Niu Z, He L, Xie Z, Wang J

Open source

DOI: 10.3389/frai.2026.1915569
Published: 2026
Container: Frontiers in artificial intelligence
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.3389/frai.2026.1915569,
  title = {An interpretable machine learning framework using multi-phase computed tomography for differentiation of adrenal lipid-poor adenomas and pheochromocytomas.},
  author = {Zhao P and Zhu F and Yan C and Niu Z and He L and Xie Z and Wang J},
  year = {2026},
  journal = {Frontiers in artificial intelligence},
  doi = {10.3389/frai.2026.1915569},
  url = {https://doi.org/10.3389/frai.2026.1915569}
}

RIS

TY  - JOUR
TI  - An interpretable machine learning framework using multi-phase computed tomography for differentiation of adrenal lipid-poor adenomas and pheochromocytomas.
AU  - Zhao P
AU  - Zhu F
AU  - Yan C
AU  - Niu Z
AU  - He L
AU  - Xie Z
AU  - Wang J
PY  - 2026
JO  - Frontiers in artificial intelligence
DO  - 10.3389/frai.2026.1915569
UR  - https://doi.org/10.3389/frai.2026.1915569
ER  -

APA

P, Z., F, Z., C, Y., Z, N., L, H., Z, X., & J, W. (2026). An interpretable machine learning framework using multi-phase computed tomography for differentiation of adrenal lipid-poor adenomas and pheochromocytomas.. Frontiers in artificial intelligence. https://doi.org/10.3389/frai.2026.1915569

Source records

pubmed · retrieved 2026-09-25T23:45:25.649Z
europe-pmc · retrieved 2026-09-25T23:45:25.656Z
doaj · retrieved 2026-09-25T23:45:25.662Z