Machine learning applications have the real potential to aid clinical practice.

Julius Gervelmeyer

Julius Gervelmeyer uses machine learning to investigate the time-course of Age-related Macular Degeneration. He is a PhD student and a scholar of the program "ClinBrAIn: Artificial Intelligence for Clinical Brain Research". Through his work analysing medical imaging data, 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.

Gervelmeyer, J., Müller, S., Huang, Z., & Berens, P.

Fundus Image Toolbox: A Python package for fundus image processing

Gervelmeyer, J., Müller, S., Djoumessi, K., Merle, D., Clark, S. J., Koch, L., & Berens, P.

Julius Gervelmeyer

Fundus Image Toolbox: A Python package for fundus image processing

Interpretable-by-design Deep Survival Analysis for Disease Progression Modeling