Multicenter deep learning model for pancreatic cancer detection using endoscopic ultrasound

doi:10.4251/wjgo.119889

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World Journal of Gastrointestinal Oncology

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1948-5204

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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 Gastrointest Oncol. Sep 15, 2026; 18(9): 119889
Published online Sep 15, 2026. doi: 10.4251/wjgo.119889

Table 1 Baseline demographic and clinical characteristics of the study population, n (%)

Characteristics	Total cohort (n = 383)	Beijing Friendship Hospital (n = 302)	Beijing Tiantan Hospital (n = 81)
Age (years), mean ± SD	66.7 ± 12.5	67.2 ± 12.2	64.8 ± 13.1
Gender
Male	202 (52.7)	162 (53.6)	40 (49.4)
Female	181 (47.3)	140 (46.4)	41 (50.6)
Class distribution
Cancerous	225 (58.7)	181 (59.9)	44 (54.3)
Noncancerous	158 (41.3)	121 (40.1)	37 (45.7)
Lesion subtypes
Cancerous group
Pancreatic ductal adenocarcinoma	219 (57.2)	176 (58.3)	43 (53.1)
Pancreatic acinar cell carcinoma	6 (1.6)	5 (1.7)	1 (1.2)
Noncancerous group
Solid pseudopapillaryoma	72 (18.8)	56 (18.5)	16 (19.8)
Autoimmune pancreatitis	55 (14.4)	41 (13.6)	14 (17.3)
Neuroendocrine neoplasms	31 (8.1)	24 (7.9)	7 (8.6)

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Citation: Yu XY, Ye JQ, He Z, He Q. Multicenter deep learning model for pancreatic cancer detection using endoscopic ultrasound. World J Gastrointest Oncol 2026; 18(9): 119889
URL: https://www.wjgnet.com/1948-5204/full/v18/i9/119889.htm
DOI: https://dx.doi.org/10.4251/wjgo.119889

Yu XY, Ye JQ, He Z, He Q. Multicenter deep learning model for pancreatic cancer detection using endoscopic ultrasound. World J Gastrointest Oncol 2026; 18(9): 119889 [DOI: 10.4251/wjgo.119889]

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