Radiomics and deep learning predict neoadjuvant immunochemotherapy response in locally advanced esophageal squamous cell carcinoma

doi:10.3748/wjg.124166

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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) 2026. 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. Dec 14, 2026; 32(46): 124166
Published online Dec 14, 2026. doi: 10.3748/wjg.124166

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Figure 5 Confusion matrices of the radiomics-deep learning model in the training, internal validation, and external validation cohorts at the Youden-derived threshold of 0. 4173. A: Training; B: Internal validation; C: External validation. Values are presented as counts (percentages of the cohort).

Citation: Zhao BX, Zhang M, Fu WQ, Li XY, Han ML, Zhang J, Gao W, Guo TH, Li HY, Ai SW, Wang HJ, Zhang BY, Wang Q. Radiomics and deep learning predict neoadjuvant immunochemotherapy response in locally advanced esophageal squamous cell carcinoma. World J Gastroenterol 2026; 32(46): 124166
URL: https://www.wjgnet.com/1007-9327/full/v32/i46/124166.htm
DOI: https://dx.doi.org/10.3748/wjg.124166

Zhao BX, Zhang M, Fu WQ, Li XY, Han ML, Zhang J, Gao W, Guo TH, Li HY, Ai SW, Wang HJ, Zhang BY, Wang Q. Radiomics and deep learning predict neoadjuvant immunochemotherapy response in locally advanced esophageal squamous cell carcinoma. World J Gastroenterol 2026; 32(46): 124166 [DOI: 10.3748/wjg.124166]

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