TABLE 1.

Optimum Hyperparameters and Performance of all Models (N = 223 images)

Model	Optimum Hyperparameters			Classification Performance (95% CI)
	Batch Size	Learning Rate	Threshold	Precision	Sensitivity	F1 Score
VGG19	16	0.001	0.39	0.88 (0.83–0.93)	0.70 (0.63–0.77)	0.78 (0.72–0.84)
DenseNet121	32	0.001	0.53	0.61 (0.54–0.68)	0.85 (0.80–0.90)	0.71 (0.64–0.78)
RestNet50	16	0.0001	0.60	0.57 (0.49–0.65)	0.85 (0.80–0.90)	0.68 (0.61–0.75)
Ensemble	N/A	N/A	0.60	0.91 (0.87–0.95)	0.77 (0.81–0.83)	0.83 (0.77–0.89)