Breast Cancer Detection

Breast cancer is among the leading causes of cancer-related deaths among women globally. Earlydetection significantly increases the chances of successful treatment and survival. This study presents adeep learning-based approach using the ResNet50 convolutional neural network (CNN) model for theautomated classification of breast cancer from ultrasound images. The system is deployed as a webapplication to facilitate real-time diagnosis support. Experimental evaluation demonstrates high accuracy,sensitivity, and specificity, indicating the model's effectiveness in differentiating malignant, benign, andnormal breast tissue.