Performance of radiomics model
A total of 3,384 ultrasonographic features were extracted from the ultrasound images. 1728 features were found to be significantly different between the two groups, through inter- and intra-observer analyses and the Mann-Whitney Spearman correlation coefficients were calculated for the eight selected features in Radiomics model, and their respective coefficient values. The longer x-axis variables of individual feature denoted that it played the more important role in the model.The Receiver operating characteristic (ROC) curves of the five models. (A) Five ML model ROC curves in the training cohort. (B) Three model ML ROC curves in the testing cohort.Performance of the three models.ACC: Accuracy; SEN: sensitivity; SPE: specificity; PPV: positive predictive value;NPV: negative predictive value; AUC: area under curve.