Multimodal deep learning integrating ultrasonographic and clinical data for enhanced rotator cuff tear identification

Ye Jiang, Huining Xu, Yuxuan Hu, Mengyao Xu, Jinping Wang, Tianyou Xin

Open source

DOI: 10.3389/fphys.2026.1884047
Published: 2026-09-11
Container: Frontiers in Physiology
Publisher: Frontiers Media SA
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.3389/fphys.2026.1884047,
  title = {Multimodal deep learning integrating ultrasonographic and clinical data for enhanced rotator cuff tear identification},
  author = {Ye Jiang and Huining Xu and Yuxuan Hu and Mengyao Xu and Jinping Wang and Tianyou Xin},
  year = {2026},
  journal = {Frontiers in Physiology},
  doi = {10.3389/fphys.2026.1884047},
  url = {https://doi.org/10.3389/fphys.2026.1884047}
}

RIS

TY  - JOUR
TI  - Multimodal deep learning integrating ultrasonographic and clinical data for enhanced rotator cuff tear identification
AU  - Ye Jiang
AU  - Huining Xu
AU  - Yuxuan Hu
AU  - Mengyao Xu
AU  - Jinping Wang
AU  - Tianyou Xin
PY  - 2026
JO  - Frontiers in Physiology
DO  - 10.3389/fphys.2026.1884047
UR  - https://doi.org/10.3389/fphys.2026.1884047
ER  -

APA

Jiang, Y., Xu, H., Hu, Y., Xu, M., Wang, J., & Xin, T. (2026). Multimodal deep learning integrating ultrasonographic and clinical data for enhanced rotator cuff tear identification. Frontiers in Physiology. https://doi.org/10.3389/fphys.2026.1884047

Source records

crossref · retrieved 2026-09-26T17:34:20.316Z