Estimating prognosis of gastric neuroendocrine neoplasms using machine learning: A step towards precision medicine

doi:10.4251/wjgo.v16.i12.4548

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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

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World J Gastrointest Oncol. Dec 15, 2024; 16(12): 4548-4552
Published online Dec 15, 2024. doi: 10.4251/wjgo.v16.i12.4548

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Figure 1 Construction of random survival forest model and Cox proportional hazards model. g-NEN: Gastric neuroendocrine neoplasm; AJCC: American Joint Committee on Cancer; LNR: Lymph node ratio; C-index: Concordance Index; AUC: Area under the curve; DCA: Decision curve analysis; RSF: Random survival forest; CoxPH: Cox proportional hazards.

Citation: Wang HN, An JH, Zong L. Estimating prognosis of gastric neuroendocrine neoplasms using machine learning: A step towards precision medicine. World J Gastrointest Oncol 2024; 16(12): 4548-4552
URL: https://www.wjgnet.com/1948-5204/full/v16/i12/4548.htm
DOI: https://dx.doi.org/10.4251/wjgo.v16.i12.4548