Constructing a prediction model for delayed wound healing after gastric cancer radical surgery based on three machine learning algorithms

doi:10.4251/wjgo.v17.i10.111163

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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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World J Gastrointest Oncol. Oct 15, 2025; 17(10): 111163
Published online Oct 15, 2025. doi: 10.4251/wjgo.v17.i10.111163

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Figure 2 Confusion matrix. A-C: Training set models: Decision tree (A); Logistic regression (B); Support vector machine (C); D-F: Validation set models: Decision tree (D); Logistic regression (E); Support vector machine (F).

Citation: An Y, Sun YG, Feng S, Wang YS, Chen YY, Jiang J. Constructing a prediction model for delayed wound healing after gastric cancer radical surgery based on three machine learning algorithms. World J Gastrointest Oncol 2025; 17(10): 111163
URL: https://www.wjgnet.com/1948-5204/full/v17/i10/111163.htm
DOI: https://dx.doi.org/10.4251/wjgo.v17.i10.111163

An Y, Sun YG, Feng S, Wang YS, Chen YY, Jiang J. Constructing a prediction model for delayed wound healing after gastric cancer radical surgery based on three machine learning algorithms. World J Gastrointest Oncol 2025; 17(10): 111163 [PMID: 41114117 DOI: 10.4251/wjgo.v17.i10.111163]

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