Construction and evaluation of a liver cancer risk prediction model based on machine learning

doi:10.4251/wjgo.v16.i9.3839

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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

Retrospective Cohort Study

World J Gastrointest Oncol. Sep 15, 2024; 16(9): 3839-3850
Published online Sep 15, 2024. doi: 10.4251/wjgo.v16.i9.3839

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Figure 1 Study design. HCC: Hepatocellular carcinoma; LR: Logistic regression; SVM: Support vector machine; RF: Random forest; LASSO: Least absolute shrinkage and selection operator; ROC: Receiver operating characteristic; DCA: Decision curve analysis.

Citation: Wang YY, Yang WX, Du QJ, Liu ZH, Lu MH, You CG. Construction and evaluation of a liver cancer risk prediction model based on machine learning. World J Gastrointest Oncol 2024; 16(9): 3839-3850
URL: https://www.wjgnet.com/1948-5204/full/v16/i9/3839.htm
DOI: https://dx.doi.org/10.4251/wjgo.v16.i9.3839

Wang YY, Yang WX, Du QJ, Liu ZH, Lu MH, You CG. Construction and evaluation of a liver cancer risk prediction model based on machine learning. World J Gastrointest Oncol 2024; 16(9): 3839-3850 [PMID: 39350987 DOI: 10.4251/wjgo.v16.i9.3839]

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