Explainable machine learning model integrating clinical and radiomic features for predicting acute suppurative cholecystitis

Figure 3 Receiver operating characteristic curves, decision curve analysis plots and, calibration analysis for the three models in the training, test, and external validation cohorts. A: Panels illustrate the diagnostic performance (area under the receiver operating characteristic curve) of the clinical model, radiomics model, and fusion model across different cohorts; B: Panels compare the net benefit of each model across the cohorts; C: Panels show the agreement between predicted probabilities and observed outcomes for each model. The fusion model consistently outperformed the individual models in all cohorts, indicating the complementary value of clinical and radiomics features. AUC: Area under the receiver operating characteristic curve.