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Prediction of Prognosis and Survival of Patients with Gastric Cancer by Weighted Improved Random Forest Model
2021
Archives of Medical Science
IntroductionIt's very necessary to predict the survival status of patients based on their prognosis. This can assist physicians in evaluating treatment decisions. Random Forest is an excellent machine learning algorithm even without any modification. We propose a new Random Forest weighting method and apply it to the gastric cancer patient data from the Surveillance, Epidemiology, and End Results (SEER) program, and then evaluated the generalization ability of this weighted Random Forest
doi:10.5114/aoms/135594
pmid:36160349
pmcid:PMC9479734
fatcat:g5m7norxbvfd7fuwuvx3oqyvkm