[165]mAlexNetAccuracy: 97.92%, Sensitivity: 98.20%, Specificity: 97.68%, Precision: 97.32%, F1 score: 97.76%SARS-CoV-2 Ct-Scan Dataset: 2482 chest CT scans[165]mAlexNet + TSA-ANNAccuracy: 98.54%, Sensitivity: 97.75%, Specificity: 99.23%, Precision: 99.09%, F1 score: 98.41%[166]mAlexNet + BiLSTMAccuracy: 98.70%COVID-19 Radiography Database[167]DC-Net-RVFLAccuracy: 90.91%, Sensitivity: 85.68%, Specificity: 96.13%, Precision: 95.70%, F1 score: 90.41%A Private Dataset: 296 lung window images[168]ResNet18Accuracy: 86.70%, Precision: 80.80%, Recall: 81.50%, F1 score: 81.10%A Private Dataset: 618 chest CT samples[169]ResNet50Accuracy: 76%, Specificity: 61.50%, Recall: 81.10%, AUC: 0.8190A Private Dataset: 495 chest CT images [170]Modified ResNet50V2Accuracy: 98.49%, Recall: 96.83%COVID-Ctset: 63849 chest CT images[171]ResNet50 + Data augmentations + CGANAccuracy: 82.91%, Sensitivity: 77.66%, Specificity: 87.62%.COVID-19 CT Scan Digital Images Dataset: 742 chest CT images[97]ResNet50+Attention+mixupAccuracy: 95.57%COVID-CT Dataset: 1596 chest CT images[172]CO-IRv2 AdamAccuracy: 94.97%, Specificity: 96.52%, Precision: 96.90%, F1-Score: 95.24%, Recall: 93.63%, Execution Time(sec): 717A New Dataset: 2481 chest CT images[172]CO-IRv2 NadamAccuracy: 96.18%, Specificity: 95.08%, Precision: 95.35%, F1-Score: 96.28%, Recall: 97.23%, Execution Time(sec): 707[172]CO-IRv2 RMSPropAccuracy: 96.18%, Specificity: 99.18%, Precision: 99.16%, F1-Score: 96.13%, Recall: 93.28%, Execution Time(sec): 749[173]DenseNet-121Accuracy: 92%, Recall: 95% A Real Patient Image Dataset: 2482 chest CT images[175]PAM-DenseNetAccuracy: 94.29%, Sensitivity: 95.74%, Specificity: 96.77%, Precision: 93.75%Dataset 1: A Lung CT Slices Dataset, 3530 chest CT slices
Dataset 2: A Lung CT Scans Dataset, 280 chest CT scans[176]VGG-19Accuracy: 94.52%COVID-19 CT Dataset: 738 chest CT scan images[177]SRGAN +VGG16Accuracy: 98.0%, Sensitivity: 99.0%, Specificity: 94.9%COVID-CT-Dataset: 470 chest CT images[178]AVNCThe sensitivity, precision, F1 all above 95%A Private Dataset: 1164 slice images [179]GoogleNetAccuracy: 82.14%COVID-CT-Dataset: 349 chest CT images[180]GoogleNet-CODAccuracy: 87.50%, Sensitivity: 90.91%, Specificity: 84.09%A Private COVID-19 Dataset: 148 chests CT images [181]5L-DCNN-SP-CAccuracy: 93.64%, Sensitivity: 93.28%, Specificity: 94.00%, Precision: 93.96%, F1 score:93.62%A Private Dataset: 320 chest CT images[182]AlexNetAccuracy: 86.85%, Sensitivity: 80.25%, Specificity: 94.29%, F1 score: 0.85, AUC: 0.94COVID-CT-Dataset: 349 chest CT images[182]GoogleNetAccuracy: 93.83%, Sensitivity: 96.71%, Specificity: 90.57%, F1 score: 0.94, AUC: 0.96[182]ResNet-18Accuracy: 95.44%, Sensitivity: 98.99%, Specificity: 91.43%, F1 score: 0.96, AUC: 0.98[182]ResNet-50Accuracy: 93.62%, Sensitivity: 95.57%, Specificity: 91.43%, F1 score: 0.94, AUC: 0.98[182]ResNet-101Accuracy: 93.29%, Sensitivity: 96.20%, Specificity: 90.00%, F1 score: 0.94, AUC: 0.98[182]Inception-ResNet-v2Accuracy: 88.59%, Sensitivity: 89.24%, Specificity: 87.86%, F1 score: 0.89, AUC: 0.96[182]VGG-16Accuracy: 89.26%, Sensitivity: 92.83%, Specificity: 85.24%, F1 score: 0.90, AUC: 0.96[182]VGG-19Accuracy: 90.16%, Sensitivity: 87.34%, Specificity: 93.33%, F1 score: 0.90, AUC: 0.97[182]DenseNet-201Accuracy: 96.20%, Sensitivity: 95.78%, Specificity: 96.67%, F1 score: 0.96, AUC: 0.98[183]WCNN4Accuracy: 99.03%COVID-19 CT Dataset: 19685 chest CT images