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Table 2 The results were obtained by applying pre-trained models in combination with five ML classifiers

From: Detecting COVID-19 in chest images based on deep transfer learning and machine learning algorithms

Model Classifier Performance metrics (%)
Accuracy Recall Precision F1 score
DenseNet201 RF 99.44 99.44 99.45 99.44
SVM 96.48 96.48 96.50 96.50
DT 93.61 93.61 93.69 93.60
KNN 100 100 100 100
LGR 99.16 99.16 99.17 99.16
ResNet50 RF 98.14 98.14 98.17 98.15
SVM 89.9 89.9 90.29 89.88
DT 92.77 92.77 92.84 92.77
KNN 99.81 99.81 99.81 99.81
LGR 98.24 98.24 98.24 98.24
Xception RF 94.16 94.16 94.21 94.16
SVM 89.53 89.53 89.68 89.52
DT 85 85 85 84.98
KNN 99.62 99.62 99.63 99.62
LGR 97.59 97.59 97.59 97.59
VGG16 RF 99.07 99.07 99.08 99.08
SVM 90.27 90.27 90.44 90.26
DT 93.14 93.14 93.15 93.14
KNN 99.81 99.81 99.81 99.81
LGR 95.55 95.55 95.57 95.55