Multi-Class Support Vector Machine Classification for Detecting Alopecia Areata and Scalp Diseases
Studysummary In this study, researchers developed a novel image processing method using a multi-class support vector machine that achieved an 89.3% accuracy in classifying alopecia areata and related conditions, outperforming existing models in classification accuracy.
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