Predicting Health With AI - With Researcher Simon Schallmoser

How can AI predict medical conditions and personalize treatments? Simon Schallmoser, researcher at LMU and MCML, uses machine learning to forecast health risks and optimize care for patients based on their individual profiles.

His work includes a system that detects low blood sugar in diabetic drivers by analyzing their driving behavior — helping prevent accidents before they happen. This research is paving the way for more personalized, proactive, and safer healthcare.

This video is part of the project KI Trans, an initiative in collaboration with TüftelLab and Uta Hauck-Thum from Ludwig-Maximilians-Universität München, focused on equipping teachers with the essential skills to navigate AI in schools. The project is funded by the Bundesministerium für Forschung, Technologie und Raumfahrt as part of DATIpilot.