Comparison of large language models and conventional machine learning in postoperative outcome prediction: a retrospective, multi-national development and validation study.
- DOI
- 10.4097/kja.25646
- Published
- 2026 Jun
- Container
- Korean journal of anesthesiology
- Publisher
- Not recorded
- Open access
- yes
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limited evidence Score 45/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.
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Cite this work
BibTeX
@article{allodium:10.4097/kja.25646,
title = {Comparison of large language models and conventional machine learning in postoperative outcome prediction: a retrospective, multi-national development and validation study.},
author = {Lee J and Kim H and Kim L and Lim L and Lee HC and Lee H},
year = {2026},
journal = {Korean journal of anesthesiology},
doi = {10.4097/kja.25646},
url = {https://doi.org/10.4097/kja.25646}
}RIS
TY - JOUR TI - Comparison of large language models and conventional machine learning in postoperative outcome prediction: a retrospective, multi-national development and validation study. AU - Lee J AU - Kim H AU - Kim L AU - Lim L AU - Lee HC AU - Lee H PY - 2026 JO - Korean journal of anesthesiology DO - 10.4097/kja.25646 UR - https://doi.org/10.4097/kja.25646 ER -
APA
J, L., H, K., L, K., L, L., HC, L., & H, L. (2026). Comparison of large language models and conventional machine learning in postoperative outcome prediction: a retrospective, multi-national development and validation study.. Korean journal of anesthesiology. https://doi.org/10.4097/kja.25646
Source records
- pubmed · retrieved 2026-09-27T08:29:54.521Z