Skin Cancer Detection Based on YOLOv8 Through A Mobile Application

Skin cancer is a type of cancer that can cause death and has a high mortality rate. Detecting this disease in its early stages is extremely important to prevent the worst effects. However, detection by a dermatologist is time-consuming and costly. Computer vision and image processing techniques can help dermatologists understand medical images. Deep learning strategies have been repeatedly used in computer vision and image processing techniques. YOLO((You Only Look Once) is one of the well-known deep learning models used to solve detection cases for small, medium, and large objects. This study evaluates the performance of YOLOv8 for skin cancer detection using the HAM10000 dataset. The proposed method achieved an accuracy rate of $92.80 \%$. These results suggest the use of YOLO, a large object detection model, to detect skin cancer at an early stage, which can be considered a reference for future research.