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
- 2026-08
- Container
- Quantitative Imaging in Medicine and Surgery
- Publisher
- AME Publishing Company
- Open access
- unknown
Credibility signals
uncertain Score 64/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.
Show all credibility signals
- supportingDOI registered: A matching record was returned by Crossref.
- supportingDOI resolves: A matching record was returned by Crossref.
- not scoredDirectory of Open Access Journals: No matching DOAJ record was present in this response. No allow-list match; this is not evidence of low credibility.
- not scoredMEDLINE indexed: Not checked or no result supplied; no credibility inference made.
- not scoredOpenAlex core source: Not checked or no result supplied; no credibility inference made.
- not scoredKnown publisher allow-list: Not checked or no result supplied; no credibility inference made.
- not scoredROR affiliation: Not checked or no result supplied; no credibility inference made.
- not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredRetraction Watch expression of concern: No expression of concern notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredRetraction Watch correction: No correction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredRetraction Watch reinstatement: No reinstatement notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredOpen access status: Not checked or no result supplied; no credibility inference made.
- not scoredPublication license: Not checked or no result supplied; no credibility inference made.
- not scoredPublication version: A publication version was supplied but is not scored.
- supportingMetadata completeness: All 6 scored descriptive metadata groups are present.
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 = {Rui Nie and Yuanyang Deng and Anhai Wei and Aowen Duan and Zhenwei Du and Hehua Zhang},
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 - Rui Nie AU - Yuanyang Deng AU - Anhai Wei AU - Aowen Duan AU - Zhenwei Du AU - Hehua Zhang 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
Nie, R., Deng, Y., Wei, A., Duan, A., Du, Z., & Zhang, H. (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
- crossref · retrieved 2026-11-09T09:46:50.123Z