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Fig. 4 | Journal of Translational Medicine

Fig. 4

From: A prognostic nomogram integrating novel biomarkers identified by machine learning for cervical squamous cell carcinoma

Fig. 4

The time‐dependent ROC curve, and overall survival based on the prognostic classifier in the training set and validation set. a In the training set, the time-dependent ROC curve analysis showed the area under the curve (AUC) for OS at 1-, 2-, 3- and 5-year was 0.817, 0.817, 0.839 and 0.787, respectively, b high-risk score significantly predicted poor OS (log‐rank test p = 0.016). c In the validation set, the AUC for OS at 1-, 2-, 3- and 5-year was 0.714, 0.691, 0.619 and 0.603, respectively, d high risk score significantly predicted poor OS (log‐rank test p = 0.028)

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