Abstract
The application of deep learning methods to diagnose diseases has become a new research topic in the medical field. In the field of medicine, skin disease is one of the most common diseases, and its visual representation is more prominent compared with the other types of diseases. Accordingly, the use of deep learning methods for skin disease image recognition is of great significance and has attracted the attention of researchers. In this study, we review 45 research efforts on the identification of skin disease by using deep learning technology since 2016. We analyze these studies from the aspects of disease type, data set, data processing technology, data augmentation technology, model for skin disease image recognition, deep learning framework, evaluation indicators, and model performance. Moreover, we summarize the traditional and machine learning-based skin disease diagnosis and treatment methods. We also analyze the current progress in this field and predict four directions that may become the research topic in the future. Our results show that the skin disease image recognition method based on deep learning is better than those of dermatologists and other computer-aided treatment methods in skin disease diagnosis, especially the multi deep learning model fusion method has the best recognition effect.
Highlights
The skin, the largest organ of the human body, is an important barrier
This study investigates the research status of skin disease recognition in recent years, summarizes the datasets used by researchers, and analyses from the aspects of image preprocessing, data augmentation, deep learning model, and framework performance indicators
This study mainly summarizes the research and application progress of skin disease image recognition based on deep learning
Summary
The skin, the largest organ of the human body, is an important barrier. The main function of the skin is to protect the human body from harmful substances from the outside world and prevent the outflow of various nutrients in the human body [1]. This study facilitates researchers to quickly and accurately retrieve the literature related to dermatological image recognition This survey’s foundation is the rapidly developing artificial intelligencebased diagnosis technology in the medical field, which has become increasing popular among researchers. This study mainly summarizes the research and application progress of skin disease image recognition based on deep learning. METHOD In recent years, deep learning has been given great attention to skin disease recognition, and research achievements increased. [“Convolutional Neural Network” and “Melanoma Recognition”] or [“Convolutional Neural Network” and “Acne Classification”] or [“Convolutional Neural Network” and “Pigmented Skin Disease Classification”] In this way, 312 papers related to deep learning are screened out and are suitable for the field of skin disease recognition.
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