Leveraging machine learning for early recurrence prediction in hepatocellular carcinoma: A step towards precision medicine

doi:10.3748/wjg.v30.i5.424

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Feb 7, 2024 (publication date) through Nov 4, 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. Feb 7, 2024; 30(5): 424-428
Published online Feb 7, 2024. doi: 10.3748/wjg.v30.i5.424

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Figure 1 Construction of random survival forests model. 15 factors used to construct random survival forests model in hepatocellular carcinoma patients who underwent R0 resection with variable importance factors emergence and risk stratification applied. HCC: Hepatocellular carcinoma; AFP: Alpha-fetoprotein.

Citation: Ravikulan A, Rostami K. Leveraging machine learning for early recurrence prediction in hepatocellular carcinoma: A step towards precision medicine. World J Gastroenterol 2024; 30(5): 424-428
URL: https://www.wjgnet.com/1007-9327/full/v30/i5/424.htm
DOI: https://dx.doi.org/10.3748/wjg.v30.i5.424