Skip to main content
Fig. 3 | Breast Cancer Research

Fig. 3

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. 3

Performance of the RDeepNet model for recurrence risk prediction in patients with different therapy regimens. Kaplan–Meier curves of RFS according to the RDeepNet model in the subgroups of patients with a endocrine therapy and b HER2-targeted therapy. ROC curves and 1-, 2-, 3-year AUCs were used to assess the prognostic accuracy of the RDeepNet model in the subgroups of patients with c endocrine therapy and d HER2-targeted therapy. 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; HER2, human epidermal growth factor receptor 2; RFS, recurrence-free survival; ROC, receiver operating characteristic

Back to article page

Breast Cancer Research

ISSN: 1465-542X

Contact us