Skin Disease Detection: A Quick and Clear Approach

Skin diseases are a global problem, affecting millions and posing serious health risks. Diagnosing these diseases can be tough, needing careful exams, medical history reviews, and lab tests. As diseases get more complex, spotting them becomes harder. This research uses a deep learning model with transfer learning to quickly identify skin diseases like chickenpox, measles, and monkeypox. A pre-trained VGG16 model helps spot disease patterns in skin images. The model was tested on images of chickenpox, measles, monkeypox, and normal skin.

It showed 93. 29% accuracy in identifying diseases. But this model can't explain how it works. Deep learning models are like black boxes, which can limit their use in healthcare. To make this system useful for healthcare, the research uses layer-wise relevance propagation (LRP) to understand why the model makes certain predictions. This helps doctors make quick and informed decisions about treating skin diseases.

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