Governing Generative Artificial Intelligence in Anatomy Education: A Proposed Risk-Tiered Framework for Donor-Derived Material, Anatomical Fidelity, and Assessment.

Mahgoub A, Singh A, Mahgoub A

DOI: 10.7759/cureus.115656
Published: 2026 Sep
Container: Cureus
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.7759/cureus.115656,
  title = {Governing Generative Artificial Intelligence in Anatomy Education: A Proposed Risk-Tiered Framework for Donor-Derived Material, Anatomical Fidelity, and Assessment.},
  author = {Mahgoub A and Singh A and Mahgoub A},
  year = {2026},
  journal = {Cureus},
  doi = {10.7759/cureus.115656},
  url = {https://doi.org/10.7759/cureus.115656}
}

RIS

TY  - JOUR
TI  - Governing Generative Artificial Intelligence in Anatomy Education: A Proposed Risk-Tiered Framework for Donor-Derived Material, Anatomical Fidelity, and Assessment.
AU  - Mahgoub A
AU  - Singh A
AU  - Mahgoub A
PY  - 2026
JO  - Cureus
DO  - 10.7759/cureus.115656
UR  - https://doi.org/10.7759/cureus.115656
ER  -

APA

A, M., A, S., & A, M. (2026). Governing Generative Artificial Intelligence in Anatomy Education: A Proposed Risk-Tiered Framework for Donor-Derived Material, Anatomical Fidelity, and Assessment.. Cureus. https://doi.org/10.7759/cureus.115656

Source records

pubmed · retrieved 2026-11-10T06:31:12.343Z