Construction and validation of machine learning-based predictive model for colorectal polyp recurrence one year after endoscopic mucosal resection

doi:10.3748/wjg.v31.i11.102387

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Mar 21, 2025 (publication date) through Apr 3, 2025

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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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World J Gastroenterol. Mar 21, 2025; 31(11): 102387
Published online Mar 21, 2025. doi: 10.3748/wjg.v31.i11.102387

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Figure 3 Decision curves of the eXtreme Gradient Boosting model across various datasets. A: Training set; B: Validation set; C: Prospective set. XGBoost: EXtreme Gradient Boosting.

Citation: Shi YH, Liu JL, Cheng CC, Li WL, Sun H, Zhou XL, Wei H, Fei SJ. Construction and validation of machine learning-based predictive model for colorectal polyp recurrence one year after endoscopic mucosal resection. World J Gastroenterol 2025; 31(11): 102387
URL: https://www.wjgnet.com/1007-9327/full/v31/i11/102387.htm
DOI: https://dx.doi.org/10.3748/wjg.v31.i11.102387