Trustworthy Decision Making with Uncertainty Quantification in AI-Assisted Medical Measurements
As Artificial Intelligence (AI) becomes a more prevalent technology in many medical measurement applications, some directly or indirectly affecting human safety, the issue of making trustworthy decisions based on AI prediction becomes important, and in some cases vital. In this talk, we will see how uncertainty can be quantified in AI-assisted medical measurements, specifically Machine Learning regression and classification, and how it can be used to catch less-trustworthy predictions, leading to more accurate and trustworthy systems that can be deployed in the real world.