Explainable machine learning for predicting grade ≥3 treatment-related adverse events in resectable non-small cell lung cancer receiving neoadjuvant chemoimmunotherapy: predominant contribution of hematologic toxicity
- DOI
- 10.21037/tlcr-2026-0984
- 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-2026-0984,
title = {Explainable machine learning for predicting grade ≥3 treatment-related adverse events in resectable non-small cell lung cancer receiving neoadjuvant chemoimmunotherapy: predominant contribution of hematologic toxicity},
author = {Fei-Hang Zhi and Yunzeng Zhang and Tengfei Ge and Lei Yang and Yichen Dong and Jialiang Wen and Haojie Si and Jingyu Chen and Yuzhou Wang and Delun Yang and Yicheng Wang and Minglei Yang and Huikang Xie and Junqi Wu and Long Xu and Deping Zhao and Chang Chen},
year = {2026},
journal = {Translational Lung Cancer Research},
doi = {10.21037/tlcr-2026-0984},
url = {https://doi.org/10.21037/tlcr-2026-0984}
}RIS
TY - JOUR TI - Explainable machine learning for predicting grade ≥3 treatment-related adverse events in resectable non-small cell lung cancer receiving neoadjuvant chemoimmunotherapy: predominant contribution of hematologic toxicity AU - Fei-Hang Zhi AU - Yunzeng Zhang AU - Tengfei Ge AU - Lei Yang AU - Yichen Dong AU - Jialiang Wen AU - Haojie Si AU - Jingyu Chen AU - Yuzhou Wang AU - Delun Yang AU - Yicheng Wang AU - Minglei Yang AU - Huikang Xie AU - Junqi Wu AU - Long Xu AU - Deping Zhao AU - Chang Chen PY - 2026 JO - Translational Lung Cancer Research DO - 10.21037/tlcr-2026-0984 UR - https://doi.org/10.21037/tlcr-2026-0984 ER -
APA
Zhi, F., Zhang, Y., Ge, T., Yang, L., Dong, Y., Wen, J., Si, H., Chen, J., Wang, Y., Yang, D., Wang, Y., Yang, M., Xie, H., Wu, J., Xu, L., Zhao, D., & Chen, C. (2026). Explainable machine learning for predicting grade ≥3 treatment-related adverse events in resectable non-small cell lung cancer receiving neoadjuvant chemoimmunotherapy: predominant contribution of hematologic toxicity. Translational Lung Cancer Research. https://doi.org/10.21037/tlcr-2026-0984
Source records
- crossref · retrieved 2026-11-09T13:42:12.609Z