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 5 Ablation study results on the internal validation set

Methods	Precision (%) (95%CI)↑	Sensitivity (%) (95%CI)↑	Accuracy (%) (95%CI)↑	Specificity (%) (95%CI)↑	F1 score (%) (95%CI)↑
GFE^b	86.85 (82.25-91.39)	88.10 (83.76-92.56)	86.41 (82.82-89.74)	84.44 (79.28-89.64)	87.47 (83.99-90.70)
LFE^b	88.73 (84.46-92.72)	90.00 (85.92-93.97)	88.46 (85.13-91.54)	86.67 (81.82-91.33)	89.36 (86.15-92.38)
LFE + CSA^b	90.05 (85.86-93.91)	90.48 (86.57-94.45)	89.49 (86.41-92.56)	88.33 (83.60-92.90)	90.26 (87.12-93.15)
LFE + GFE^a	90.09 (85.32-93.24)	95.24 (91.54-97.66)	91.50 (87.95-93.85)	86.75 (81.71-91.33)	92.59 (89.20-94.48)
MCEUS-C2Net (ours)	93.46 (89.08-95.97)	97.09 (95.48-99.51)	94.51 (92.31-96.67)	91.14 (86.70-94.92)	95.24 (93.01-97.01)

^aP < 0.05 vs MCEUS-C2Net.

^bP < 0.01 vs MCEUS-C2Net.

Accuracy, precision, sensitivity, specificity, and F1 score are presented as (%). 95% confidence interval were calculated using the bootstrapping method with 1000 resamples. Statistical significance was evaluated using McNemar’s test, and all P values were adjusted for multiple comparisons using the Benjamini-Hochberg false discovery rate procedure. CSA: Channel self-attention; GFE: Global feature extraction; LFE: Local feature extraction; CI: Confidence interval.

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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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