Artificial intelligence (AI) could fundamentally transform clinical workflows in image-based diagnostics and population screening. AI promises more objective, accurate and effective analysis of medical images, improving the early detection of disease. Health services are overstretched and under significant pressure, so advanced technological solutions are urgently needed. However, a major hurdle in using medical imaging AI in clinical practice is the assurance whether it is safe for patients and continues to be safe after deployment. Differences in patient populations and changes in the data acquisition pose challenges to today’s AI algorithms. This Research Chair focuses on developing AI safeguards including automatic failure detection, monitoring of performance, and analysis of bias to ensure the safe and ethical use of medical imaging AI.
Ben Glocker
Professor in Machine Learning for Imaging
