T2-weighted imaging-based radiomic-clinical machine learning model for predicting the differentiation of colorectal adenocarcinoma

Figure 9 Three models (clinical, radiomic, and combined models) were used to predict the calibration curve of colorectal cancer differentiation in the training cohort and the validation cohort. A: Calibration curves for the training cohort; B: Calibration curves for the validation cohort. The straight line at 45° represents the standard curve with the probability of perfect matching between the actual (y-axis) and nomogram-predicted (x-axis) differentiation grade. With respect to the training cohort and the validation cohort, the predicted probabilities of the clinical model and the radiomic model closely corresponded to the actual probabilities. Rad: radiomics.