22.09.2025
Predicting Health With AI - With Researcher Simon Schallmoser
Research Film
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.
©MCML
Related
22.07.2026
MCML Welcomes Student Delegation From HEC Montréal
MCML welcomed students from HEC Montréal for discussions on AI research, ethics, and international academic collaboration.
21.07.2026
Timo Heiß Receives Best Student Paper Award at XAI 2026
Timo Heiß receives the Best Student Paper Award at XAI 2026 for research on improving feature effect estimation in explainable AI.
21.07.2026
The Learning Rate Does More Than Set the Pace
New ICML 2026 research by Gitta Kutyniok and her team shows how learning rates balance competing biases that shape neural network generalization.