Machine learning and radiomics for differentiating severe from moderately severe acute necrotizing pancreatitis on contrast-enhanced computed tomography

doi:10.4240/wjgs.v18.i5.115903

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World Journal of Gastrointestinal Surgery

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1948-9366

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

Retrospective Cohort Study

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 Surg. May 27, 2026; 18(5): 115903
Published online May 27, 2026. doi: 10.4240/wjgs.v18.i5.115903

Table 2 Characteristics of moderately severe and severe acute necrotizing pancreatitis patients in the training cohort, n (%)/mean ± SD/median (interquartile rage)

Characteristics		MSAP (n = 76)	SAP (n = 52)	Z/χ²/t/Fisher’s exact test	P value
Age (years)		45.01 ± 13.58	52.88 ± 14.68	-3.116	0.002^b
Gender	Male	50 (65.79)	34 (65.38)	0.002	0.962
Gender	Female	26 (34.21)	18 (34.62)	0.002	0.962
Alcohol consumption history	No	47 (61.84)	37 (71.15)	1.187	0.276
Alcohol consumption history	Yes	29 (38.16)	15 (28.85)	1.187	0.276
WBC (× 10⁹/L)		14.12 ± 4.21	15.47 ± 6.24	-1.369	0.175
Serum amylase (× 10 U/L)		23.80 (7.18-43.35)	47.31 (10.83-116.60)	-2.159	0.031^a
Serum lipase (× 10 U/L)		27.45 (11.23-94.00)	59.41 (15.76-117.91)	-1.356	0.175
MCTSI score		8.00 (6.50-8.00)	8.00 (8.00-10.00)	-2.879	0.004^b
Pancreatic necrosis types	Only pancreatic parenchymal necrosis type	11 (14.47)	5 (9.62)	0.730	0.781
	Mixed type	60 (78.95)	44 (84.61)
	Only peripancreatic necrosis type	5 (6.58)	3 (5.77)

^aP < 0.05.

^bP < 0.01.

WBC: White blood cell; MCTSI: Modified Computed Tomography Severity Index; MSAP: Moderately severe acute pancreatitis; SAP: Severe acute pancreatitis.

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Citation: Feng Y, Hu XH, Xiao B. Machine learning and radiomics for differentiating severe from moderately severe acute necrotizing pancreatitis on contrast-enhanced computed tomography. World J Gastrointest Surg 2026; 18(5): 115903
URL: https://www.wjgnet.com/1948-9366/full/v18/i5/115903.htm
DOI: https://dx.doi.org/10.4240/wjgs.v18.i5.115903

Feng Y, Hu XH, Xiao B. Machine learning and radiomics for differentiating severe from moderately severe acute necrotizing pancreatitis on contrast-enhanced computed tomography. World J Gastrointest Surg 2026; 18(5): 115903 [DOI: 10.4240/wjgs.v18.i5.115903]

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