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The radiomics features were significantly associated with the histopathological grading. Quantitative imaging features (n=1409) were extracted, and nine features were selected to predict the grades of meningiomas. The best performance of the radiomics model for the degree of differentiation was obtained by SVM (area under the curve (AUC), 0.956; 95% confidence interval (CI), 0.83-1.00; sensitivity, 0.87; specificity, 0.92; f1-score, 0.9. The radiomics models are of great value in predicting the histopathological grades of meningiomas, a
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