Predicting chemotherapy-induced myelosuppression in colorectal cancer: An interpretable, machine learning-based nomogram

doi:10.3748/wjg.v31.i42.112180

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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. Nov 14, 2025; 31(42): 112180
Published online Nov 14, 2025. doi: 10.3748/wjg.v31.i42.112180

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Figure 4 Mean importance of candidate predictors. A: Random forest algorithm; B: Decision trees algorithm. BSA: Body surface area; BMI: Body mass index; T: Tumor; N: Node; M: Metastasis; HM: Hepatic metastasis; LM: Lung metastasis; PM: Peritoneal metastasis; ALB: Albumin; CEA: Carcinoembryonic antigen; CA: Carbohydrate antigen.

Citation: Liu YM, Du YY, Song Y, Xiong HT, Yu HB, Li BH, Cai L, Ma SS, Gao J, Zhang HY, Fang RY, Cai R, Zheng HG. Predicting chemotherapy-induced myelosuppression in colorectal cancer: An interpretable, machine learning-based nomogram. World J Gastroenterol 2025; 31(42): 112180
URL: https://www.wjgnet.com/1007-9327/full/v31/i42/112180.htm
DOI: https://dx.doi.org/10.3748/wjg.v31.i42.112180

Liu YM, Du YY, Song Y, Xiong HT, Yu HB, Li BH, Cai L, Ma SS, Gao J, Zhang HY, Fang RY, Cai R, Zheng HG. Predicting chemotherapy-induced myelosuppression in colorectal cancer: An interpretable, machine learning-based nomogram. World J Gastroenterol 2025; 31(42): 112180 [PMID: 41278162 DOI: 10.3748/wjg.v31.i42.112180]

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