Towards Bayesian Uncertainty Quantification in Deep Learning Models for Brain Tumor Segmentation

Presenters: Xun Huan, Assistant Professor, Mechanical Engineering While the use of deep learning models in healthcare has grown rapidly in recent years, the uncertainty and confidence in their predictions is often unavailable and unreported. A lack of such information can render decision-making dangerous, and prompt clinicians to hesitate in using and trusting these machine learning technologies. Listen to Prof. Huan (Mechanical Engineering) explains how his team is tackling this issue using principles and