Hybrid deep learning ensemble model for detecting small to medium rotator cuff tears from shoulder radiographs.

Jhan SW, Huang TH, Cheng JH, Wu KT, Chou WY, Tsai JT, Ho WH

DOI: 10.1186/s13018-026-06890-5
Published: 2026 Jun 16
Container: Journal of orthopaedic surgery and research
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.1186/s13018-026-06890-5,
  title = {Hybrid deep learning ensemble model for detecting small to medium rotator cuff tears from shoulder radiographs.},
  author = {Jhan SW and Huang TH and Cheng JH and Wu KT and Chou WY and Tsai JT and Ho WH},
  year = {2026},
  journal = {Journal of orthopaedic surgery and research},
  doi = {10.1186/s13018-026-06890-5},
  url = {https://doi.org/10.1186/s13018-026-06890-5}
}

RIS

TY  - JOUR
TI  - Hybrid deep learning ensemble model for detecting small to medium rotator cuff tears from shoulder radiographs.
AU  - Jhan SW
AU  - Huang TH
AU  - Cheng JH
AU  - Wu KT
AU  - Chou WY
AU  - Tsai JT
AU  - Ho WH
PY  - 2026
JO  - Journal of orthopaedic surgery and research
DO  - 10.1186/s13018-026-06890-5
UR  - https://doi.org/10.1186/s13018-026-06890-5
ER  -

APA

SW, J., TH, H., JH, C., KT, W., WY, C., JT, T., & WH, H. (2026). Hybrid deep learning ensemble model for detecting small to medium rotator cuff tears from shoulder radiographs.. Journal of orthopaedic surgery and research. https://doi.org/10.1186/s13018-026-06890-5

Source records

pubmed · retrieved 2026-09-26T23:58:02.726Z