irAE-GPT: leveraging large language models to identify immune-related adverse events in electronic health records and clinical trial datasets.
- DOI
- 10.1016/j.ebiom.2026.106227
- Published
- 2026 May
- Container
- EBioMedicine
- Publisher
- Not recorded
- Open access
- yes
Credibility signals
limited evidence Score 45/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.
Show all credibility signals
- cautionDOI registered: No matching Crossref record was present in this response.
- cautionDOI resolves: No matching Crossref record was present in this response.
- 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.
- supportingOpen access status: Normalized open-access status: open.
- 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.
- cautionMetadata completeness: 5 of 6 scored descriptive metadata groups are present; missing fields increase uncertainty.
Cite this work
BibTeX
@article{allodium:10.1016/j.ebiom.2026.106227,
title = {irAE-GPT: leveraging large language models to identify immune-related adverse events in electronic health records and clinical trial datasets.},
author = {Bejan CA and Wang M and Venkateswaran S and Bergmann EA and Hiles L and Xu Y and Chandler GS and Brondfield S and Silverstein J and Wright F and de Dios K and Kim DM and Mukherjee E and Krantz MS and Yao L and Johnson DB and Phillips EJ and Balko JM and Mohindra R and Quandt Z},
year = {2026},
journal = {EBioMedicine},
doi = {10.1016/j.ebiom.2026.106227},
url = {https://doi.org/10.1016/j.ebiom.2026.106227}
}RIS
TY - JOUR TI - irAE-GPT: leveraging large language models to identify immune-related adverse events in electronic health records and clinical trial datasets. AU - Bejan CA AU - Wang M AU - Venkateswaran S AU - Bergmann EA AU - Hiles L AU - Xu Y AU - Chandler GS AU - Brondfield S AU - Silverstein J AU - Wright F AU - de Dios K AU - Kim DM AU - Mukherjee E AU - Krantz MS AU - Yao L AU - Johnson DB AU - Phillips EJ AU - Balko JM AU - Mohindra R AU - Quandt Z PY - 2026 JO - EBioMedicine DO - 10.1016/j.ebiom.2026.106227 UR - https://doi.org/10.1016/j.ebiom.2026.106227 ER -
APA
CA, B., M, W., S, V., EA, B., L, H., Y, X., GS, C., S, B., J, S., F, W., K, D. D., DM, K., E, M., MS, K., L, Y., DB, J., EJ, P., JM, B., R, M., & Z, Q. (2026). irAE-GPT: leveraging large language models to identify immune-related adverse events in electronic health records and clinical trial datasets.. EBioMedicine. https://doi.org/10.1016/j.ebiom.2026.106227
Source records
- pubmed · retrieved 2026-09-25T13:27:23.743Z