Comparison of Machine Learning-Based Reporting with Surgeon Reporting of Postoperative Complication in Cardiothoracic Morbidity and Mortality Conferences.
- DOI
- 10.1097/xcs.0000000000002179
- Published
- 2026 Aug 27
- Container
- Journal of the American College of Surgeons
- Publisher
- Not recorded
- Open access
- unknown
Credibility signals
limited evidence Score 43/100 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.
- 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.
- cautionMetadata completeness: 5 of 6 scored descriptive metadata groups are present; missing fields increase uncertainty.
Cite this work
BibTeX
@article{allodium:10.1097/xcs.0000000000002179,
title = {Comparison of Machine Learning-Based Reporting with Surgeon Reporting of Postoperative Complication in Cardiothoracic Morbidity and Mortality Conferences.},
author = {Healy GL and Shen G and Colborn KL and Henderson WG and Chauhan A and Cleveland JC Jr and Meguid RA},
year = {2026},
journal = {Journal of the American College of Surgeons},
doi = {10.1097/xcs.0000000000002179},
url = {https://doi.org/10.1097/xcs.0000000000002179}
}RIS
TY - JOUR TI - Comparison of Machine Learning-Based Reporting with Surgeon Reporting of Postoperative Complication in Cardiothoracic Morbidity and Mortality Conferences. AU - Healy GL AU - Shen G AU - Colborn KL AU - Henderson WG AU - Chauhan A AU - Cleveland JC Jr AU - Meguid RA PY - 2026 JO - Journal of the American College of Surgeons DO - 10.1097/xcs.0000000000002179 UR - https://doi.org/10.1097/xcs.0000000000002179 ER -
APA
GL, H., G, S., KL, C., WG, H., A, C., Jr, C. J., & RA, M. (2026). Comparison of Machine Learning-Based Reporting with Surgeon Reporting of Postoperative Complication in Cardiothoracic Morbidity and Mortality Conferences.. Journal of the American College of Surgeons. https://doi.org/10.1097/xcs.0000000000002179
Source records
- pubmed · retrieved 2026-09-26T18:58:12.683Z