Retrieval-augmented generation models for predicting pathological upgrading in endoscopically resected gastric low-grade intraepithelial neoplasia: A dual-center evaluation

doi:10.3748/wjg.122422

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World Journal of Gastroenterology

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1007-9327

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Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA

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Copyright: ©Author(s) 2027. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial (CC BY-NC 4.0) license. No commercial re-use. See permissions. Published by Baishideng Publishing Group Inc.

World J Gastroenterol. Jan 7, 2027; 33(1): 122422
Published online Jan 7, 2027. doi: 10.3748/wjg.122422

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Figure 2 Model discriminative performance. Receiver operating characteristic curves for the retrieval-augmented generation-enhanced large language models and experienced endoscopists in predicting pathological upgrading in gastric low-grade intraepithelial neoplasia. AUC: Area under the receiver operating characteristic curve; 95%CI: 95% confidence interval; GLM: Generalized linear mixed.

Citation: Zhuang Q, Cheng JN, Zheng YL, Wu S, Chu YM, Zhou L, Xia J, Ning M, Peng HX, Wan XJ, Dong ZX. Retrieval-augmented generation models for predicting pathological upgrading in endoscopically resected gastric low-grade intraepithelial neoplasia: A dual-center evaluation. World J Gastroenterol 2027; 33(1): 122422
URL: https://www.wjgnet.com/1007-9327/full/v33/i1/122422.htm
DOI: https://dx.doi.org/10.3748/wjg.122422

Zhuang Q, Cheng JN, Zheng YL, Wu S, Chu YM, Zhou L, Xia J, Ning M, Peng HX, Wan XJ, Dong ZX. Retrieval-augmented generation models for predicting pathological upgrading in endoscopically resected gastric low-grade intraepithelial neoplasia: A dual-center evaluation. World J Gastroenterol 2027; 33(1): 122422 [DOI: 10.3748/wjg.122422]

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