Table 7.

Comparison of dense dropout deep learning models for cancer detection performance

Model	Precision
	Adenocarcinoma	Large-Cell	Normal	Squamous cell	Average
EffiecientNetB3-Dense-Dropout	0.87	0.76	0.85	1.00	0.87
ResNet-50-Dense-Dropout	0.91	0.9	0.92	1.00	0.93
ResNet-101-Dense-Dropout	0.96	0.8	1.00	1.00	0.94
Score-level fusion model	0.92	0.9	0.92	1.00	0.94
Model	Recall
	Adenocarcinoma	Large-Cell	Normal	Squamous cell	Average
EffiecientNet-B3-Dense-Dropout	0.91	1.00	1.00	0.65	0.89
ResNet-50-Dense-Dropout	1.00	0.90	1.00	0.83	0.89
ResNet-101-Dense-Dropout	0.95	1.00	1.00	0.79	0.93
Score-level fusion model	1.00	1.00	1.00	0.75	0.94
Model	F1-Score
	Adenocarcinoma	Large-Cell	Normal	Squamous cell	Average
EffiecientNet-B3-Dense-Dropout	0.89	0.86	0.92	0.79	0.87
ResNet-50-Dense-Dropout	0.95	0.9	0.96	0.91	0.87
ResNet-101-Dense-Dropout	0.96	0.89	1	0.88	0.93
Score-level fusion model	0.96	0.95	0.96	0.86	0.93