Bid farewell to single indicators: Machine learning models integrating multidimensional data lead thrombosis risk prediction into a new stage

doi:10.3748/wjg.118337

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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. Sep 14, 2026; 32(34): 118337
Published online Sep 14, 2026. doi: 10.3748/wjg.118337

Table 1 Clinical applicability comparison (machine learning models vs traditional markers)

Model category	Internal AUC	External AUC	Overall performance	Clinical applicability
CatBoost (best ML model)	0.818	0.815	Excellent	Highly recommended
Other ML models (average)	0.792	0.79	Good	Recommended
D-dimer (traditional marker)	0.618	0.51	Poor	Not recommended

AUC: Area under the curve; ML: Machine learning.

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Citation: Su Y, Wang DX, Zhao YQ, Xing X. Bid farewell to single indicators: Machine learning models integrating multidimensional data lead thrombosis risk prediction into a new stage. World J Gastroenterol 2026; 32(34): 118337
URL: https://www.wjgnet.com/1007-9327/full/v32/i34/118337.htm
DOI: https://dx.doi.org/10.3748/wjg.118337

Su Y, Wang DX, Zhao YQ, Xing X. Bid farewell to single indicators: Machine learning models integrating multidimensional data lead thrombosis risk prediction into a new stage. World J Gastroenterol 2026; 32(34): 118337 [DOI: 10.3748/wjg.118337]

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