Skip to main content

Table 3 Sensitivity, specificity and AUC obtained from previously trained models inferring on the external validation cohort with corresponding data correction

From: Prediction of lipomatous soft tissue malignancy on MRI: comparison between machine learning applied to radiomics and deep learning

Dataset Classifier Sensitivity (%) Specificity (%) AUC
Images ResNet50 92 24 0.64
Radiomics LR 1 0 0.50
SVM 70 32 0.47
RF 64 68 0.71
GB 67 64 0.70
Radiomics with batch correction LR 1 0.07 0.54
SVM 47 57 0.48
RF 53 86 0.75
GB 97 61 0.80
  1. AUC area under the curve, CNN convolutional neural networks, FE feature extraction, XGB Xgboost, GB gradient boosting, LR logistic regression, RF random forest, SVM support vector machine