Table 3.

Classification accuracy of different methods on the ISIC2017 dataset.

	Average	Nevus classification
Method	AC	AC	F1-score	Pre	SP
Swin Transformer Liu et al. (2021)	80.22	89.50	81.18	62.16	91.76
AION Gehlot and Gupta (2021)	81.55	85.33	76.01	50.74	86.86
TransMed Dai et al. (2021)	84.11	89.19	80.10	61.90	92.16
MobileNetV3 Howard et al. (2019)	84.89	89.33	81.53	60.83	90.78
EfficientNet-B3 Tan and Le (2019)	85.22	90.67	82.64	66.67	93.33
Inception v4 Szegedy et al. (2016)	85.33	89.16	81.45	60.16	90.39
ResNet50 He et al. (2016)	85.44	91.00	82.97	68.37	93.92
DenseNet201 Huang et al. (2017)	86.56	92.00	85.36	69.81	93.73
O-Net	87.22	91.67	83.51	72.73	95.29
	Average	Melanoma classification				Keratosis classification
Method	AC	AC	F1-score	Pre	SP	AC	F1-score	Pre	SP
Swin Transformer Liu et al. (2021)	80.22	73.00	71.63	84.07	73.91	78.17	68.45	45.33	83.02
AION Gehlot and Gupta (2021)	81.55	77.33	75.69	85.40	74.40	82.00	69.73	54.46	90.48
TransMed Dai et al. (2021)	84.11	79.17	77.13	84.72	71.50	84.00	79.83	59.63	55.56
MobileNetV3 Howard et al. (2019)	84.89	80.50	78.78	86.51	75.36	84.83	74.59	62.75	92.13
EfficientNet-B3 Tan and Le (2019)	85.22	80.50	78.82	86.70	75.85	84.50	75.71	59.84	89.86
Inception v4 Szegedy et al. (2016)	85.33	80.83	79.05	86.39	74.88	86.00	75.94	67.37	93.58
ResNet50 He et al. (2016)	85.44	81.50	79.99	87.90	78.26	83.83	75.28	57.69	88.61
DenseNet201 Huang et al. (2017)	86.56	83.50	81.55	86.57	73.91	84.17	72.48	61.96	92.75
O-Net	87.22	84.17	81.58	84.49	67.63	85.83	74.19	70.00	95.03

Bold font to highlight the optimal values.