Background: Onychomycosis is a common disease. Emerging noninvasive, real-time techniques such as dermoscopy and deep convolutional neural networks have been proposed for the diagnosis of onychomycosis. However, deep learning application in dermoscopic images has not been reported.
Objectives:To explore the establishment of deep learning-based diagnostic models for onychomycosis in dermoscopy to improve the diagnostic efficiency and accuracy.
Methods:We evaluated the dermoscopic patterns of onychomycosis diagnosed at
Exophiala spinifera is a rare dematiaceous fungus causing cutaneous, subcutaneous and disseminated phaeohyphomycosis (PHM). Standard antifungal therapy for PHM is still uncertain. Here, we report a case of a Chinese male with PHM caused by E. spinifera, who received significant clinical improvement after the treatment with oral itraconazole and terbinafine. With the aim of evaluating the antifungal therapy for PHM caused by E. spinifera, a detailed review was performed.
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