Detection and Classification of Skin Cancer Using YOLOv8n

Skin cancer is a disease caused by the growth of abnormal cells in skin tissues. The World Health Organization (WHO) has recorded an 88% increase in deaths due to skin cancer caused by exposure to ultraviolet rays. Currently, in the medical field, the diagnosis of skin cancer involves a biopsy process, which requires considerable time and cost. Therefore, this study aims to develop a system for detecting and classifying skin cancer based on the shape of skin lesions using the You Only Look Once version 8 nano (YOLOv8n), which can detect lesions rapidly. The dataset used is ISIC 2019, comprising of 4289 images of cancerous skin lesions divided into 9 classes: Basal Cell Carcinoma, Squamous Cell Carcinoma, Melanoma, Actinic Keratosis, Dermatofibroma, Nevus, Seborrheic Keratosis, Pigmented Benign Keratosis, and Vascular Lesion. Experimental results show that the designed system performs well in detecting and classifying the lesions, achieving an overall accuracy of 93.5%, with a Precision of 93.5%, Recall of 93.7<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">%</sup>, and an F1-Score of 93.5%.