Pulmonary lesion subtypes recognition of COVID-19 from radiomics data with three-dimensional texture characterization in computed tomography images

Table 1 Performance of COVID-19 classification achieved by SVM, KNN, LR, GaussianNB, QDA, RF, HAFS-RF (\(\alpha =0.5\))

Method	Label	Precision (%)	Recall (%)	Accuracy (%)	F-measure (%)
SVM	1	76.34	99.42	82.3	86.37
	2	99.48	62.07	92.31%	76.45
	3	100.0	57.75	98.04	73.21
	4	96.84	58.2	91.75	72.71
KNN	1	88.04	86.32	85.66	87.17
	2	83.09	83.23	93.19	83.16
	3	78.05	86.49	98.17	82.05
	4	65.98	67.96	87.58	66.96
LR	1	83.46	88.4	83.8	85.86
	2	76.93	75.3	89.83	76.11
	3	66.67	52.11	96.58	58.5
	4	55.86	50.27	83.7	52.92
GaussianNB	1	88.57	59.6	72.88	71.25
	2	42.62	62.72	75.52	50.75
	3	14.64	86.62	76.01	25.05
	4	37.82	10.19	79.89	16.05
QDA	1	95.14	36.67	63.72	52.94
	2	39.1	97.27	66.82	55.78
	3	100.0	99.3	99.97	99.65
	4	43.38	48.66	79.07	45.87
DT	1	91.85	92.57	91.49	92.21
	2	91.53	87.21	95.53	89.32
	3	86.75	90.34	98.89	88.51
	4	78.36	79.93	91.79	79.14
RF	1	89.70	93.31	90.42	91.47
	2	84.92	83.59	93.48	84.25
	3	86.11	87.94	98.79	87.02
	4	80.78	72.53	91.30	76.43
HAFS-RF (our)	1	92.21	95.52	93.06	93.84
	2	93.17	91.58	96.84	92.37
	3	95.14	95.8	99.58	95.47
	4	88.43	80.75	94.3	84.42

Bold values indicate the maximum value of each type of lesion classification index

ISSN: 1475-925X