Research on Classification of COVID-19 Chest X-Ray Image Modal Feature Fusion Based on Deep Learning

Table 6

Comparative study of the proposed model 2 with existing works with respect to accuracy, precision, recall and F1-score.

Author	Type of images	Architecture	Classes	Accuracy (%)	F1-score (%)	Precision (%)	Recall (%)
Sethy and Behera [20]	Chest X-ray	ResNet50 + SVM	2	95.33	95.34	—	—
Hemdan et al. [31]	Chest X-ray	VGG19	2	90.00	90.00	91.50	90.00
		DenseNet201	2	90.00	90.00	91.50	90.00
Kumar et al. [17]	Chest X-ray	DeQueezeNet	2	94.52	—	90.48	96.15
Jaiswal et al. [34]	Chest X-ray	COVIDPEN	2	96.00	94.00	92.00	96.00
Ismael and Şengür [30]	Chest X-ray	ResNet50 + SVM	2	94.70	94.79	—	91.00
Das [33]	Chest X-ray	DenseNet201 + Resnet50V2 + Inceptionv3	2	91.62	—	—	95.09
Sahinbas and Catak [32]	Chest X-ray	VGG16	2	80.00	80.00	80.00	80.00
This study	Chest X-ray	Model 2	2	96.00	95.50	96.10	96.42