Application of preoperative artificial neural network based on blood biomarkers and clinicopathological parameters for predicting long-term survival of patients with gastric cancer

doi:10.3748/wjg.v25.i43.6451

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Nov 21, 2019 (publication date) through Jul 15, 2024

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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 21, 2019; 25(43): 6451-6464
Published online Nov 21, 2019. doi: 10.3748/wjg.v25.i43.6451

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Figure 4 Survival curves of the clinical TNM staging. A: The discrimination between the survival curves of each stage of the clinical TNM (cTNM) system in the training set was good (P < 0.05). B: There was no significant difference in the survival curves between the cTNM stages I and II A (P = 0.935), and between stages III and IVA (P = 0.355). cTNM: Clinical TNM.

Citation: Que SJ, Chen QY, Qing-Zhong, Liu ZY, Wang JB, Lin JX, Lu J, Cao LL, Lin M, Tu RH, Huang ZN, Lin JL, Zheng HL, Li P, Zheng CH, Huang CM, Xie JW. Application of preoperative artificial neural network based on blood biomarkers and clinicopathological parameters for predicting long-term survival of patients with gastric cancer. World J Gastroenterol 2019; 25(43): 6451-6464
URL: https://www.wjgnet.com/1007-9327/full/v25/i43/6451.htm
DOI: https://dx.doi.org/10.3748/wjg.v25.i43.6451