Cancer research

Cancer research

Risk Assessment Models for Venous Thromboembolism in Cancer Patients Show Limited Discriminatory Performance

Cancer patients undergoing contemporary systemic anticancer therapies are at high risk of developing venous thromboembolism (VTE), a potentially life-threatening condition. To identify patients with high VTE risk who may benefit from primary thromboprophylaxis, several risk assessment models (RAMs) have been developed. However, the performance of these RAMs has not been

Cancer research

Deep Learning Models Show Promising Potential in Breast Cancer Diagnosis

A recent study published in the Frontiers in Medicine journal has found that deep learning models, particularly convolutional neural networks (CNNs) and transformer-based architectures, demonstrate excellent performance in classifying breast cancer pathology images. The research highlights the potential of these models in enhancing clinical decision-making in breast cancer management. According