Martin Lillholm

Martin Lillholm is a Professor at the Department of Computer Science, University of Copenhagen, specializing in Image Analysis, Computational Modelling, and Geometry. His research focuses on leveraging machine learning and deep learning for medical imaging, particularly in breast cancer risk stratification and COVID-19 adverse outcome prediction. He has co-authored numerous high-impact journal articles in Radiology, Scientific Reports, and other venues, often collaborating with clinical researchers.

Research Trends & Fields

Lillholm’s work bridges computer science and healthcare, with recent publications emphasizing:

• AI-driven mammography screening for early breast cancer detection
• Texture analysis in medical images to enhance risk prediction
• Domain adaptation for robust cross-vendor imaging systems
• Health registry analysis using machine learning for recurrent cancer identification
• Pandemic risk modeling for COVID-19 outcomes

Collaborations & Impact

He collaborates across disciplines, including with Department of Clinical Medicine researchers and international partners. His studies have been widely cited, with significant visibility via Mendeley, X, and news outlets. While no formal awards are listed, his research has driven clinical protocol innovations and policy discussions.