A Nomogram Combining MRI Multisequence Radiomics and Clinical Factors for Predicting Recurrence of High-Grade Serous Ovarian Carcinoma

Figure 2

(a) Nomogram based on radiomics signatures and clinical factors. In the nomogram, a vertical line was made according to each parameter to determine the corresponding value of points. The total points were the sum of the three points above. Then, a vertical line was made according to the value of the total points to predict the recurrence probability of HGSOC. (b–d) Model’s performance assessment and comparison. (b) Decision curve analysis of radiomics signature, clinical model, and nomogram, respectively. (c) Receiver operating characteristic curve analysis in the validation cohorts. (d) Delong test for the given models.

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