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Peer-reviewedCC BYFrontiers in digital health

Evaluating artificial intelligence-generated clinical guidance for patellar dislocation: accuracy, readability and qualitative appraisal of DeepSeek-R1 responses

  • Shuo Liu1
  • Xiyang Sun1
  • Yunfei Ma2
  • Zhenzhong Yang3
  • Hanyuan Zhang1
  • Hongbo Mao1
  • Bin Xu1
  1. 1Department of Orthopedics, Department of Sports Medicine and Arthroscopic Surgery, The First Affiliated Hospital of Anhui Medical University , ,
  2. 2First School of Clinical Medicine, Anhui Medical University , ,
  3. 3Department of Orthopedics, Department of Sports Medicine and Arthroscopic Surgery, The Fourth People's Hospital of Lu'an , ,
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Cite

BibTeXRIS
BibTeX
@article{liu2026evaluating,
  title = {{Evaluating artificial intelligence-generated clinical guidance for patellar dislocation: accuracy, readability and qualitative appraisal of DeepSeek-R1 responses}},
  author = {Shuo Liu and Xiyang Sun and Yunfei Ma and Zhenzhong Yang and Hanyuan Zhang and Hongbo Mao and Bin Xu},
  journal = {Frontiers in digital health},
  year = {2026},
  month = oct,
  url = {https://europepmc.org/article/PMC/PMC13658195},
  note = {CC BY},
}
RIS
TY  - JOUR
TI  - Evaluating artificial intelligence-generated clinical guidance for patellar dislocation: accuracy, readability and qualitative appraisal of DeepSeek-R1 responses
AU  - Shuo Liu
AU  - Xiyang Sun
AU  - Yunfei Ma
AU  - Zhenzhong Yang
AU  - Hanyuan Zhang
AU  - Hongbo Mao
AU  - Bin Xu
PY  - 2026
DA  - 2026/10/16
JO  - Frontiers in digital health
UR  - https://europepmc.org/article/PMC/PMC13658195
SN  - 2673-253X
ER  -