Skin Disease Diagnostic techniques using deep learning

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Abstract

On our planet, skin cancer is among the most dangerous diseases. It is, however, difficult to diagnose skin cancer correctly. A variety of tasks have recently been shown to be excelled by machine learning and deep learning algorithms. In the case of skin diseases, these algorithms are very useful. In this article, we examine various machine learning and deep learning techniques and their use in diagnosing skin diseases. In this paper, we discuss common skin diseases and the method of acquiring images from dermatology, and we present several freely available datasets. Our focus shifts to exploring popular machine learning and deep learning architectures and popular frameworks for implementing machine and deep learning algorithms once we have introduced machine learning and deep learning concepts. Following that, performance evaluation metrics are presented. Here we are going to review the literature on machine and deep learning and how these technologies can be used to detect skin diseases. Furthermore, we discuss potential research directions and the challenges in the area. In this paper, the principal goal is to describe contemporary machine learning and deep learning methods for skin disease diagnosis

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