AIMC Topic: Dermatomycoses

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

Pathology, research and practice
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. ...

Novel B-DNA dermatophyte assay for demonstration of canonical DNA in dermatophytes: Histopathologic characterization by artificial intelligence.

Clinics in dermatology
We describe a novel assay and artificial intelligence-driven histopathologic approach identifying dermatophytes in human skin tissue sections (ie, B-DNA dermatophyte assay) and demonstrate, for the first time, the presence of dermatophytes in tissue ...

Automated detection of superficial fungal infections from microscopic images through a regional convolutional neural network.

PloS one
Direct microscopic examination with potassium hydroxide is generally used as a screening method for diagnosing superficial fungal infections. Although this type of examination is faster than other diagnostic methods, it can still be time-consuming to...

Superficial Fungal Infections and Artificial Intelligence: A Review on Current Advances and Opportunities: REVISION.

Mycoses
BACKGROUND: Superficial fungal infections are among the most common infections in world, they mainly affect skin, nails and scalp without further invasion. Superficial fungal diseases are conventionally diagnosed with direct microscopy, fungal cultur...

Next generation mycological diagnosis: Artificial intelligence-based classifier of the presence of Malassezia yeasts in tape strip samples.

Mycoses
BACKGROUND: Malassezia yeasts are almost universally present on human skin worldwide. While they can cause diseases such as pityriasis versicolor, their implication in skin homeostasis and pathophysiology of other dermatoses is still unclear. Their a...