Iterative Prompt Refinement Improves Large Language Model Extraction of Operative Note Data: A Pilot Validation Study.
- DOI
- 10.1016/j.gassur.2026.102602
- Published
- 2026 Sep 17
- Container
- Journal of gastrointestinal surgery : official journal of the Society for Surgery of the Alimentary Tract
- Publisher
- Not recorded
- Open access
- unknown
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limited evidence Score 43/100 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:10.1016/j.gassur.2026.102602,
title = {Iterative Prompt Refinement Improves Large Language Model Extraction of Operative Note Data: A Pilot Validation Study.},
author = {Wang C and Maric E and Burt M and Wada K and Liu N and Ujiki M},
year = {2026},
journal = {Journal of gastrointestinal surgery : official journal of the Society for Surgery of the Alimentary Tract},
doi = {10.1016/j.gassur.2026.102602},
url = {https://doi.org/10.1016/j.gassur.2026.102602}
}RIS
TY - JOUR TI - Iterative Prompt Refinement Improves Large Language Model Extraction of Operative Note Data: A Pilot Validation Study. AU - Wang C AU - Maric E AU - Burt M AU - Wada K AU - Liu N AU - Ujiki M PY - 2026 JO - Journal of gastrointestinal surgery : official journal of the Society for Surgery of the Alimentary Tract DO - 10.1016/j.gassur.2026.102602 UR - https://doi.org/10.1016/j.gassur.2026.102602 ER -
APA
C, W., E, M., M, B., K, W., N, L., & M, U. (2026). Iterative Prompt Refinement Improves Large Language Model Extraction of Operative Note Data: A Pilot Validation Study.. Journal of gastrointestinal surgery : official journal of the Society for Surgery of the Alimentary Tract. https://doi.org/10.1016/j.gassur.2026.102602
Source records
- pubmed · retrieved 2026-09-26T04:25:29.470Z