Skin disease diagnosis with deep learning: A review

Skin cancer is one of the most threatening diseases worldwide. However, diagnosing skin correctly challenging. Recently, deep learning algorithms have emerged to achieve excellent performance in various tasks. Particularly, they been applied disease diagnosis In this paper, we present a review on methods and their applications diagnosis. We first brief introduction image acquisition dermatology, list several publicly available datasets. Then, introduce conception learning, popular architectures frameworks facilitating implementation algorithms. Thereafter, evaluation metrics are presented. As an important part article, then literature involving for from aspects according specific Additionally, discuss challenges faced area suggest possible future research directions. The major purpose article provide conceptual systematically recent works with learning. Given popularity there remains great area, as well opportunities that can explore future.