Novel Crow Swarm Optimization Algorithm and Selection Approach for Optimal Deep Learning COVID-19 Diagnostic Model

Table 9

CSO results for 10 runs.

Fitness	AUC	CAR	F1-score	Precision	Recall	FPR	PPV	NPV	MSE	Speed	Angle
The results of the first dataset
71.82	14.45	17.46	10.59	8.50	10.16	9.63	5.72	5.19	18.28	0.69	53
81.32	14.76	12.38	17.45	9.11	10.53	6.66	5.77	3.49	19.81	0.77	129
77.12	14.26	18.53	13.51	7.51	9.96	8.46	6.05	3.42	18.27	−3.43	53
70.41	13.72	16.09	9.28	7.80	9.46	9.49	6.76	5.36	22.02	−2.22	45
77.73	14.30	18.10	11.57	12.52	6.01	6.87	4.06	4.13	22.42	−2.08	131
72.54	14.32	18.19	8.71	12.45	11.10	8.41	4.04	4.16	18.58	3.89	59
73.34	13.85	11.17	10.51	10.37	8.70	8.18	6.76	3.92	26.51	−3.31	57
73.57	15.19	11.23	10.65	9.18	9.31	7.60	8.09	6.78	21.94	3.99	67
78.56	14.73	17.97	9.035	13.52	10.27	5.60	6.08	3.17	19.60	2.46	57
76.20	15.55	12.41	11.11	13.38	7.11	7.33	6.25	3.65	23.17	−2.92	48
75.26	14.51	15.35	11.24	10.43	9.26	7.82	5.96	4.33	21.06	−0.21	69.9
The results of the second dataset
74.26	14.18	14.50	12.00	9.93	10.21	8.70	5.11	5.50	19.85	3.71	57
79.03	13.89	12.48	13.01	14.99	9.42	5.79	4.54	6.00	19.86	2.08	46
74.31	14.15	18.68	12.20	11.80	7.76	7.64	5.38	5.44	16.93	−5.67	112
74.45	14.02	18.21	10.04	10.04	6.37	7.35	4.50	4.77	24.68	2.42	110
80.88	14.04	17.33	15.03	12.88	8.79	6.03	3.88	4.60	17.41	−0.02	56
81.85	14.19	11.93	15.54	12.34	7.44	4.91	7.71	5.72	20.20	−0.19	54
81.90	14.26	12.50	15.55	14.38	5.48	5.69	6.01	3.97	22.16	4.91	45
71.74	14.70	11.93	10.40	9.13	10.66	8.85	6.53	6.15	21.62	−2.16	87
73.61	13.37	11.87	13.22	9.56	10.16	10.21	4.09	4.20	23.31	−3.03	58
72.98	15.46	15.35	11.85	12.50	6.44	9.48	4.44	3.66	20.79	3.92	52
76.50	14.23	14.48	12.88	11.76	8.27	7.47	5.22	5.00	20.68	0.60	67.7