معرفی
Amir A Borhani is an Associate Professor in the Departments of Radiology (Body Imaging) and Surgery (Organ Transplantation) at Northwestern University. His research focuses on advancing medical imaging techniques for hepatocellular carcinoma (HCC) diagnosis, liver transplantation, and AI-driven radiology tools. He is actively involved in developing imaging biomarkers, radiomics analyses, and machine learning models for precision medicine applications.
Key research areas include LI-RADS guidelines for HCC classification, MRI segmentation algorithms (e.g., MDNet, Meddelinea), ethical AI frameworks in healthcare, and imaging of cirrhosis and post-transplant complications. His work bridges clinical practice and cutting-edge technology, emphasizing non-invasive diagnostics and predictive modeling.
Recent publications highlight advancements in tumor response assessment, AI-generated medical image validation, and global HCC surveillance strategies. He collaborates on interdisciplinary projects addressing liver disease pathophysiology and surgical outcomes.
Laboratory and team efforts include the development of deep learning models for organ segmentation, liver stiffness quantification via magnetic resonance elastography, and AI tools for improving diagnostic accuracy in abdominal imaging.
