Development and validation of a deep learning model integrating 18F-FDG PET/CT radiomics and clinical features to predict major pathological response in non-small cell lung cancer patients receiving chemoimmunotherapy
- DOI
- 10.21037/tlcr-2026-0739
- Published
- 2026-10
- Container
- Translational Lung Cancer Research
- 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/tlcr-2026-0739,
title = {Development and validation of a deep learning model integrating 18F-FDG PET/CT radiomics and clinical features to predict major pathological response in non-small cell lung cancer patients receiving chemoimmunotherapy},
author = {Ao Li and Zi-Hao Mao and Hai-Long Wang and Yuan Wang and Qi-Hui Fu and Wen-Chao Feng and Yang Chen and Yin-Ting Hu and Zhi-Hua Liu and Wen-Zhao Zhong and Lei Jiang and Ben-Yuan Jiang},
year = {2026},
journal = {Translational Lung Cancer Research},
doi = {10.21037/tlcr-2026-0739},
url = {https://doi.org/10.21037/tlcr-2026-0739}
}RIS
TY - JOUR TI - Development and validation of a deep learning model integrating 18F-FDG PET/CT radiomics and clinical features to predict major pathological response in non-small cell lung cancer patients receiving chemoimmunotherapy AU - Ao Li AU - Zi-Hao Mao AU - Hai-Long Wang AU - Yuan Wang AU - Qi-Hui Fu AU - Wen-Chao Feng AU - Yang Chen AU - Yin-Ting Hu AU - Zhi-Hua Liu AU - Wen-Zhao Zhong AU - Lei Jiang AU - Ben-Yuan Jiang PY - 2026 JO - Translational Lung Cancer Research DO - 10.21037/tlcr-2026-0739 UR - https://doi.org/10.21037/tlcr-2026-0739 ER -
APA
Li, A., Mao, Z., Wang, H., Wang, Y., Fu, Q., Feng, W., Chen, Y., Hu, Y., Liu, Z., Zhong, W., Jiang, L., & Jiang, B. (2026). Development and validation of a deep learning model integrating 18F-FDG PET/CT radiomics and clinical features to predict major pathological response in non-small cell lung cancer patients receiving chemoimmunotherapy. Translational Lung Cancer Research. https://doi.org/10.21037/tlcr-2026-0739
Source records
- crossref · retrieved 2026-11-09T18:17:07.387Z