Construction of the radiomics prediction models
gliomas
GLIOMAS, HYPERPLASIA
The LASSO, SVM and RF models were established following preprocessing of the extracted features based on the 10 times 7:3 random segmentation method. The AUC, accuracy, sensitivity, and specificity were applied to assess the performance. The precise procedure involved randomly splitting glial cell hyperplasia and gliomas into 10 portions, of which 7 were employed as the training group and 3 as the validation group. Each test can obtain the corresponding model prediction probability. The mean value of each prediction efficiency index was obtained as the final evaluation result of model efficiency after ten repetitions of 7:3 random split testing. Delong’s test was used to compare the AUC of the three models, then the radiomics model with highest efficiency was selected for further analysis.