Skin diseases are one of the most common diseases, affecting approximately 1.9 billion people worldwide, and early detection of skin diseases can help avoid deterioration and improve treatment outcomes. Existing clinical detection methods have drawbacks such as high subjectivity and complexity, as existing diagnostic algorithms pay less attention to interpretability, and research mainly focuses on Caucasian skin. Therefore, we designed a multi-spectral skin disease detection system based on multi-model multi-layer networks to accurately differentiate similar skin diseases. The results show that the system has great potential in assisting the detection of skin diseases and can effectively improve the diagnostic accuracy and medical efficiency of skin diseases.
Zou et al. (Wed,) studied this question.
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