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Fig. 2 | Breast Cancer Research

Fig. 2

From: Machine learning radiomics of magnetic resonance imaging predicts recurrence-free survival after surgery and correlation of LncRNAs in patients with breast cancer: a multicenter cohort study

Fig. 2

Performance of the RDeepNet model for predicting the recurrence risk in the training, validation, and testing cohorts. Kaplan–Meier curves of RFS according to the RDeepNet model in the a training cohort, b validation cohort, and c testing cohort. ROC curves and 1-, 2-, 3-year AUCs were used to assess the prognostic accuracy of the RDeepNet model in the d training cohort, e validation cohort, and f testing cohort. P values were calculated using the unadjusted log-rank test, and hazard ratios were calculated by a univariate Cox regression analysis. AUC, area under the receiver operating characteristics curve; CI, confidence interval; HR, hazard ratio; RFS, recurrence-free survival; ROC, receiver operating characteristic

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Breast Cancer Research

ISSN: 1465-542X

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