Machine learning-based reconstruction of prognostic staging for gastric cancer patients with different differentiation grades: A multicenter retrospective study

doi:10.3748/wjg.v31.i13.104466

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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

Retrospective Study

World J Gastroenterol. Apr 7, 2025; 31(13): 104466
Published online Apr 7, 2025. doi: 10.3748/wjg.v31.i13.104466

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Figure 2 Multivariable cox proportional hazards regression analysis of lymph node ratio staging system and pN staging system for overall survival in gastric cancer patients with different degrees of differentiation in the training set. A: Lymph node ratio staging system; B: pN staging system. WD: Well-differentiated; MD: Moderately differentiated; PD: Poorly differentiated; GC: Gastric cancer.

Citation: Zhang YL, Song HB, Xue YW. Machine learning-based reconstruction of prognostic staging for gastric cancer patients with different differentiation grades: A multicenter retrospective study. World J Gastroenterol 2025; 31(13): 104466
URL: https://www.wjgnet.com/1007-9327/full/v31/i13/104466.htm
DOI: https://dx.doi.org/10.3748/wjg.v31.i13.104466

Zhang YL, Song HB, Xue YW. Machine learning-based reconstruction of prognostic staging for gastric cancer patients with different differentiation grades: A multicenter retrospective study. World J Gastroenterol 2025; 31(13): 104466 [PMID: 40248057 DOI: 10.3748/wjg.v31.i13.104466]

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