leverage machine learning techniques to address inefficiencies and challenges in maintaining high quality in imaging-based healthcare
comprehensively assess AI by focusing on real-world clinical variables to understand model capabilities and limitations
develop strategies and recommendations to conduct robust quality assessments of AI models
build tools to detect anomalies, performance deviations, and potential risks associated
with AI deployment
Summary description
