Researcher from University of Calgary Reports Recent Findings in Breast Cancer (Malignancy pattern analysis of breast ultrasound images using clinical features and a graph convolutional network).

A recent report from the University of Calgary discusses the importance of early diagnosis in breast cancer and presents an automated analysis and classification system for breast cancer using clinical markers. The researchers used a graph convolutional network (GCN) model to classify breast tumors as benign or malignant based on clinical features. The proposed model achieved a test accuracy of 98.73% and outperformed other models in comparison. The study concludes that a GCN model using graph data shows promise as an automated feature-based breast image classification system. [Extracted from the article]