Trochanteric region fracture classification network (TRFC-net): a deep learning solution to increasing inexperienced residents' trochanteric region fracture classification accuracy on X-rays.
- DOI
- 10.21037/qims-2026-1-0353
- Published
- 2026 Aug 1
- Container
- Quantitative imaging in medicine and surgery
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.21037/qims-2026-1-0353,
title = {Trochanteric region fracture classification network (TRFC-net): a deep learning solution to increasing inexperienced residents' trochanteric region fracture classification accuracy on X-rays.},
author = {Nie R and Deng Y and Wei A and Duan A and Du Z and Zhang H},
year = {2026},
journal = {Quantitative imaging in medicine and surgery},
doi = {10.21037/qims-2026-1-0353},
url = {https://doi.org/10.21037/qims-2026-1-0353}
}RIS
TY - JOUR TI - Trochanteric region fracture classification network (TRFC-net): a deep learning solution to increasing inexperienced residents' trochanteric region fracture classification accuracy on X-rays. AU - Nie R AU - Deng Y AU - Wei A AU - Duan A AU - Du Z AU - Zhang H PY - 2026 JO - Quantitative imaging in medicine and surgery DO - 10.21037/qims-2026-1-0353 UR - https://doi.org/10.21037/qims-2026-1-0353 ER -
APA
R, N., Y, D., A, W., A, D., Z, D., & H, Z. (2026). Trochanteric region fracture classification network (TRFC-net): a deep learning solution to increasing inexperienced residents' trochanteric region fracture classification accuracy on X-rays.. Quantitative imaging in medicine and surgery. https://doi.org/10.21037/qims-2026-1-0353
Source records
- pubmed · retrieved 2026-09-25T16:52:08.644Z