Breast Cancer Prediction Using Machine Learning: A YOLOv8 Approach

Breast cancer is among the major concerns in global health, and its management starts with early diagnosis. This article presents an advanced machine learning approach with a deep learning YOLO algorithm (You Only Look Once). YOLOv8 is the definitive version of the YOLO deep learning algorithm. The breast cancer detection YOLOv8 model is based on ultrasound images. In the given case, deep learning techniques are being ended with to give detection high precision, speed, and performance. This paper presents an application of a deep learning algorithm, YOLOv8, in real-time breast cancer detection using ultrasound imaging. In comparison, this model represented higher accuracy and recall than both ResNet50 and VGG16, thereby representing good potential for its integration into clinical settings. Our model showed results of 93% accuracy and 92% recall, which exceeds the results of ResNet50 and VGG16 by 6% and 10%, respectively. Finally, we have described how the integration of this system will be implemented on a clinical level in a real-time web-based interface, closing our work and showing future work at the clinical level how this research may be a source of such advancements in the early detection of breast cancer.