Metastasis Detection

Metastasis detection research focuses on developing accurate and efficient methods for identifying the spread of cancer to other parts of the body, improving diagnosis and treatment planning. Current efforts leverage deep learning, employing architectures like U-Nets and convolutional neural networks, often trained using transfer learning and techniques to address data imbalance, to analyze various imaging modalities (CT scans, whole-slide images, MRI) and even clinical text. These advancements aim to improve diagnostic accuracy, reduce the workload on clinicians, and ultimately enhance patient outcomes by enabling earlier and more precise interventions.