Table 7.

Performance comparison of Pre-trained deep learning models for dental condition detection

Model	Dental Condition	F1-Score	Precision	Recall	Accuracy
VGG16	Cavity	0.808 ± 0.026	0.801 ± 0.026	0.815 ± 0.034	0.823 ± 0.020
	Fillings	0.831 ± 0.023	0.834 ± 0.028	0.828 ± 0.027	0.823 ± 0.020
	Impacted Tooth	0.822 ± 0.031	0.815 ± 0.023	0.830 ± 0.027	0.823 ± 0.020
	Implant	0.805 ± 0.027	0.812 ± 0.032	0.798 ± 0.033	0.823 ± 0.020
	Macro Average	0.817 ± 0.027	0.816 ± 0.027	0.818 ± 0.030	0.823 ± 0.020
Xception	Cavity	0.791 ± 0.023	0.785 ± 0.028	0.798 ± 0.025	0.809 ± 0.023
	Fillings	0.815 ± 0.026	0.818 ± 0.024	0.812 ± 0.023	0.809 ± 0.023
	Impacted Tooth	0.804 ± 0.029	0.798 ± 0.030	0.811 ± 0.034	0.809 ± 0.023
	Implant	0.791 ± 0.030	0.798 ± 0.025	0.784 ± 0.031	0.809 ± 0.023
	Macro Average	0.800 ± 0.027	0.800 ± 0.027	0.801 ± 0.028	0.809 ± 0.023
ResNet50	Cavity	0.774 ± 0.029	0.768 ± 0.021	0.781 ± 0.027	0.795 ± 0.027
	Fillings	0.798 ± 0.025	0.801 ± 0.028	0.795 ± 0.027	0.795 ± 0.027
	Impacted Tooth	0.797 ± 0.025	0.783 ± 0.025	0.812 ± 0.029	0.795 ± 0.027
	Implant	0.774 ± 0.026	0.781 ± 0.019	0.767 ± 0.029	0.795 ± 0.027
	Macro Average	0.786 ± 0.026	0.783 ± 0.023	0.789 ± 0.028	0.795 ± 0.027