Table 2.

Applicability of DL for resolving some key issues of COVID-19

Dataset/Database Considered	Technique used	Input Type	Outcomes	Reference
COVID-19 dataset	CNN	Montage of Images	Good monitoring rate	[64]
Protease dataset	Generative adversarial networks	Text data	Cost-effective	[65]
COVID Time Series data	RNN (Recurrent Neural Network), LSTM (Long Short-Term Memory), BiLSTM (Bidirectional LSTM), GRUs (Gated Recurrent Units) & VAE (Variational Auto Encoder)	Time Series data	VAE is superior to other proposed methods	[66]
Annotated dataset of COVID-19	CNN	CT images	Good assessment rate	[67]
COVID-19 Indian data	ANNAIL (ANN based Adaptive Incremental Learning)	Text data	Good mortality reduction rate	[68]
COVID-19 chest X-ray dataset	GAN (Generative Adversarial Network)	X-ray images	Reliable outcomes are obtained	[69]
COVID 19 chest CT Image data	ResNet-32	CT images	Good classification rate	[70]
COVID-19 Indian dataset	RNN based LSTM	Text data	High prediction rate	[71]
COVID-19 CT image data	Logistic regression	CT Images	Best accuracy for prediction of COVID-19 severity	[72]
COVID-19 confirmed patient data (Wuhan, China)	CNN	CT images	Good performance	[73]
COVID-19 chest X-ray dataset	VGG-16	Chest X-rays	Good detection rate	[74]
COVID-19 chest X-ray dataset	VGG-16	CT images	Good identification rate	[75]
CXR Image dataset	CNN	Image data	Better Diagnosis rate	[76]
COVID-19 CXR dataset	Resnet-101	X-ray images	97.77% accuracy	[77]
COVID-19 patients data	VGG Net	Chest radiographic Images	Good detection rate	[78]
Chest X-ray datasets	Inception (Xception) model	Chest X-ray	97% accuracy	[79]
Pneumonia CXR images dataset	CNN	Chest X-ray images	Good detection rate	[80]
CXR image COVID-19 dataset (19 Positive Patients)	Inception V3	CXR Images	Better Accuracy	[81]
Lung CT dataset	3 Dimensional U-Net	CT Images	Good segmentation rate	[82]
COVID-19 patient dataset	3 Dimensional U-Net	Chest CT Images	Good abnormality detection rate	[83]
CT Image data	V-Net	CT Images	Good detection rate has been obtained	[84]
3905 X-ray images dataset	AlexNet, VGGNet16, VGGNet19, GoogleNet, and ResNet50	X-ray Image	99.18% of classification accuracy	[85]
TCIA dataset	CNN	CT Images	Good accuracy rates	[86]
Datasets from Kaggle & Github	VGG16, ResNet50 as well as MobileNetV2	Chest X-ray (CXR) Images	Good detection rate	[87]
Data from RYDLS-20 database	CNN	Image data	Good identification rate	[88]
ZINC database	LSTM-RNN	Image data	99.62% accuracy for binary classification and 96.70% accuracy for multiclass classification are obtained	[89]
CXR image dataset	ResNet-101& ResNet-152	CXR Images	Good detection rate	[90]
Google Trends data In Iran	LSTM	Text data	Good Prediction rate	[91]
CXR image dataset	ResNet18, ResNet50	Image data	Good prediction rate	[92]
CT Image dataset of COVID-19 Patients	CNN	CT Image	99.6% accuracy	[93]
ImageNet dataset	CNN	CXR	97.62% accuracy	[94]
Kermany dataset	CNN	X-ray Image	98.08% accuracy	[95]
Not Defined	CNN	CT Image	99.02% accuracy	[96]
Cohen dataset	MobileNetV2, SqueezeNet	CXR Image	99.27% accuracy	[97]
COVID chestxray dataset	CNN	CXR	99.50% average accuracy	[98]
ImageNet dataset	Bayes-SqueezeNet	CXR Image	98.3% overall accuracy	[99]
LUS image dataset	CNN	LUS (Lung Ultrasonography) Image	Good classification rate	[100]
Not Defined	CNN	Chest CT	90.10% accuracy	[101]
COVID-19 IMAGING DATASETS	Inf-net	CT Image	Good accuracy	[102]
CXR COVID-19 dataset	CNN	CXR	Good Performance	[103]
GISAID	CNN	Text data	Good Screening rate	[104]
Pediatric, RSNA, Chexpert as well as NIH datasets	CNN	CXR	Good accuracy	[105]
CXR dataset(181 Patients data)	CNN	CXR	96.3% accuracy	[106]
RHWU Patient dataset	Resnet-50	CT Image	81.9% accuracy	[107]
6087 images of CXR & CT dataset	VGG16, VGG19, DenseNet201, Inception_ResNet_V2, Inception_V3, Resnet50 and MobileNet_V2	X-ray	Reliable accuracies	[108]