Computational Intelligence and Healthcare Informatics. Группа авторов

- - COVID-19–induced pneumonia

Table 2.3 Comparison of models on the basis of AUC score for 14 chest pathologies.

Ref.	Atel	Card	Effu	Infi	Mass	Nodu	Pne1	Pnet	Cons	Edem	Emph	Fibr	PT	Hern
[10]	0.784	0.888	0.831	0.705	0.838	0.796	0.727	0.876	0.746	0.852	0.942	0.837	0.796	0.912
[23]	0.795	0.887	0.875	0.703	0.835	0.716	0.742	0.863	0.786	0.892	0.875	0.756	0.774	0.836
[70]	0.716	0.807	0.784	0.609	0.706	0.671	0.633	0.806	0.708	0.835	0.815	0.769	0.708	0.767
[69]	0.743	0.875	0.811	0.677	0.783	0.698	0.696	0.81	0.723	0.833	0.822	0.804	0.751	0.899
[8]	-	0.940	-	-	-	-	-	-	-	-	-	-	-	-
[47]	0.909	0.910	0.964	-	-	-	-	-	0.957	0.958	-	-	-	-
[26]	0.794	0902	0.839	0.714	0.827	0.727	0.703	0.848	0.773	0.834	0.911	0.824	0.752	0.916
[20]	0.853	0.939	0.903	0.754	0.902	0.828	0.774	0.921	0.842	0.924	0.932	0.964	0.837	0.921
[74] AlexNet	0.645	0.692	0.664	0.604	0.564	0.648	0.549	0.742	-	-	-	-	-	-
GoogleNet	0.631	0.706	0.688	0.609	0.536	0.558	0.599	0.782	-	-	-	-	-	-
VGGNet-16	0.628	0.708	0.650	0.589	0.510	0.656	0.510	0.751	-	-	-