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Prediction of survival outcomes in patients with epithelial ovarian cancer using machine learning methods

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Fig. 1. Flowchart of development of the prediction model for overall survival in ovarian cancer patients
Table 1. Patient demographics and clinical characteristics of the training cohort and test cohort
Fig. 3. Comparison of the median AUC of the models generated with gradually reduced features on the Wilcoxon test
Fig. 5. Kaplan-Meier survival curves for OS in the validation cohort based on the subgroup (A, B, C, and D) according to the second-year OS probability scores  predicted by the GB model (A) and subgroup according to FIGO stage (I, II, III, and IV) (B)

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