Opportunities and Challenges: Classification of Skin Disease Based on Deep Learning

Chinese Journal of Mechanical Engineering

Jien Ma¹  Hao Zhang²  Yichen Luo²  Xue Zhou²  Huayong Yang²  Bin Zhang²  Liang Ma² 

[1] College of Electrical Engineering, Zhejiang University, 310027, Hangzhou, China;State Key Laboratory of Fluid Power and Mechatronic Systems, Zhejiang University, 310058, Hangzhou, China;School of Mechanical Engineering, Zhejiang University, 310058, Hangzhou, China;

关键词: Skin disease;    Image method;    Deep learning;    Disease classification;   

DOI  :  10.1186/s10033-021-00629-5

来源: Springer

【 摘 要 】

Deep learning has become an extremely popular method in recent years, and can be a powerful tool in complex, prior-knowledge-required areas, especially in the field of biomedicine, which is now facing the problem of inadequate medical resources. The application of deep learning in disease diagnosis has become a new research topic in dermatology. This paper aims to provide a quick review of the classification of skin disease using deep learning to summarize the characteristics of skin lesions and the status of image technology. We study the characteristics of skin disease and review the research on skin disease classification using deep learning. We analyze these studies using datasets, data processing, classification models, and evaluation criteria. We summarize the development of this field, illustrate the key steps and influencing factors of dermatological diagnosis, and identify the challenges and opportunities at this stage. Our research confirms that a skin disease recognition method based on deep learning can be superior to professional dermatologists in specific scenarios and has broad research prospects.

【 授权许可】

CC BY