This study presents a nuanced approach to the detection and classification of ten types of skin diseases, employing both ResNet-50 for feature extraction and a Support Vector Machine (SVM) with a ...

Skin diseases affect millions of people across the globe, and prevention of complications and improvement of outcomes often require promptness in diagnosis. However, the limited access to ...

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The classification report evaluates a model trained on a dataset consisting of 22 types of skin diseases. It includes metrics such as precision, recall, F1-score, and support for each disease, ...