Machine learning applications have the real potential to aid clinical practice.
Julius Gervelmeyer
Julius Gervelmeyer is a PhD student at the Department of Data Science at Hertie Institute for AI in Brain Health, University of Tübingen. He is a scholar of the program “ClinBrAIn: Artificial Intelligence for Clinical Brain Research”. Julius applies machine learning methods to analyse medical imaging data, specifically focusing on investigating the time-course of Age-related Macular Degeneration. Through his work, he aims to contribute to methods that assist clinicians in decision making, ultimately benefiting society.
Machine learning applications have the real potential to aid clinical practice.