An interpretable whole-stream video based deep learning framework for surgical skill assessment of basic procedural elements.

Chen K, Weng Y, Zhang Y, Wang B, Li Z, Tang K

DOI: 10.1097/js9.0000000000005082
Published: 2026 Jun
Container: International journal of surgery (London, England)
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.1097/js9.0000000000005082,
  title = {An interpretable whole-stream video based deep learning framework for surgical skill assessment of basic procedural elements.},
  author = {Chen K and Weng Y and Zhang Y and Wang B and Li Z and Tang K},
  year = {2026},
  journal = {International journal of surgery (London, England)},
  doi = {10.1097/js9.0000000000005082},
  url = {https://doi.org/10.1097/js9.0000000000005082}
}

RIS

TY  - JOUR
TI  - An interpretable whole-stream video based deep learning framework for surgical skill assessment of basic procedural elements.
AU  - Chen K
AU  - Weng Y
AU  - Zhang Y
AU  - Wang B
AU  - Li Z
AU  - Tang K
PY  - 2026
JO  - International journal of surgery (London, England)
DO  - 10.1097/js9.0000000000005082
UR  - https://doi.org/10.1097/js9.0000000000005082
ER  -

APA

K, C., Y, W., Y, Z., B, W., Z, L., & K, T. (2026). An interpretable whole-stream video based deep learning framework for surgical skill assessment of basic procedural elements.. International journal of surgery (London, England). https://doi.org/10.1097/js9.0000000000005082

Source records

pubmed · retrieved 2026-09-26T06:13:37.743Z