A decision support system for the detection of cutaneous fungal infections using artificial intelligence.

Cutaneous fungal infections are one of the most common skin conditions, hence, the burden of determining fungal elements upon microscopic examination with periodic acid-Schiff (PAS) and Gomori methenamine silver (GMS) stains, is very time consuming. Despite some morphological variability posing challenges to training artificial intelligence (AI)-based solutions, these structures are favored potential targets, enabling the recruitment of promising AI-based technologies. Herein, we present a novel AI solution for identifying skin fungal infections, potentially providing a decision support system for pathologists.