Table 1.

Other studies present in the literature besides those analyzed in the Discussion section of this work.

Authors	Years	Type of AI	Results	Strengths	Limits
Potter et al. [16]	1987	Interactive computer program	Concordance, 91.8% Disagreement, 4.8%	Concordance and possibility of integration with patient clinical data	Disagreement and little memory space
Crowlet R. et al. [17]	2003	Traditional intelligent tutoring system	Possibility of learning rather easily	Positive feedback	Clear prototypical schemes are indispensable
Joset Feit et al. [18]	2005	Hypertext atlas of dermatopathology	A collection of about 3200 dermatopathological images	Continuous updating	/
Payne et al. [19]	2009	Intelligent tutoring system	Tutoring made it possible to implement the training of learners	Ability to learn from mistakes	Greater difficulties in tutoring related to superficial perivascular dermatitis
Olsen et al. [20]	2018	Deep learning algorithms	The artificial intelligence system accurately classified 123/124 (99.45%) BCCs (nodular), 113/114 (99.4%) dermal nevi and 123/123 (100%) seborrheic keratoses	Concordance	Difficulty in presenting artifacts, poor coloring