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Insights into Imaging
Fig. 7 | Insights into Imaging

Fig. 7

From: A virtual biopsy study of microsatellite instability in gastric cancer based on deep learning radiomics

Fig. 7

Performance evaluation of prediction models and nomogram. Receiver operating characteristic (ROC) curves comparison of three prediction models in training (A) and testing (B) sets: Clinical characteristics model (name 1), radiomics features model (name 2), and hybrid model (name 3) of Rad-score combined with the clinical features. As shown in the figure, the hybrid model achieved the highest AUC (0.883 and 0.802) in both sets. C The calibration curve shows the calibration between the predicted risk of the MSI state and the observed result of the MSI state in the nomogram model. D The DCA of radiomics model and nomogram model. The x-axis represents the risk threshold probability, and the y-axis is the net benefits. The nomogram model showed better clinical net benefits. AUC area under the curve

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