Table 1.

Literature review of Melanoma classification using deep learning

References	Dataset	Methods	Classification	Accuracy
Antony et al. [18]	Self-collected	ANN	Melanoma	86.66%
Alquran et al. [6]	ISIC	SVM	Melanoma	92.1%
Yang et al. [4]	Self-collected	Ridge and furrow pattern	AM	99%
Esteva et al. [22]	Self-collected	Inception V3	Melanoma	72.1%
Yu et al. [10]	Yonsei University	VGG16	AM	80%
Hosny et al. [9]	PH2	AlexNet	Melanoma	98.33%
Praveenkumar and Dharmalingam [19]	Self-collected	ANN	Melanoma	97%
Li et al. [23]	ISIC	CNNs	Melanoma	82%
Salido and Ruiz [24]	PH2	Deep CNN	Melanoma	93%
Hosny et al. [15]	ISIC, DERM	AlexNet and augmentation	Melanoma	87%
Sherif et al. [25]	ISIC	Deep CNN	Melanoma	96.57%
Murugan et al. [8]	ISIC	SVM, kNN	Melanoma	89.43%, 76.87%
Kassani SH and Kassani PH [20]	ISIC	Deep CNNs	Melanoma	92%
Brinker et al. [21]	ISIC	CNNs	Melanoma	Specificity 86.5%, sensitivity 74.1%