25.06.2025
When Clinical Expertise Meets AI Innovation – With Michael Ingrisch
Research Film
Artificial intelligence has enormous potential in radiology — but realizing it requires more than good algorithms.
Michael Ingrisch, Clinical Data Science Professor at LMU and MCML PI, shares how his team took a practical approach: identifying a key diagnostic challenge in PET CT imaging and inviting the broader AI community to help solve it.
«Only if we understand both fields, AI and radiology, we can identify and map strategies to solve problems that actually need solving.»
Michael Ingrisch
MCML PI
Through an open machine learning competition, participants used real clinical data to train models for tumor segmentation. The results were tested on unseen data, with the winning solution demonstrating not just technical skill — but clinical relevance.
Ingrisch highlights the importance of interdisciplinary collaboration: without it, even the best models risk solving the wrong problems. His team is working to ensure the next generation of AI tools is not only cutting-edge — but aligned with the real needs of clinicians and patients.
This video is part of our MCML spotlight series on researchers driving AI forward through real-world impact.
©MCML
The film was produced and edited by Nicole Huminski and Nikolai Huber.
Related
29.10.2026
Teaching Language Models to Express Uncertainty
An ICLR 2026 paper shows how reinforcement learning improves confidence estimates from language models.
27.10.2026
Runner-Up Prize at AutoML 2026 for Tabular-DC-Bench
Tabular-DC-Bench, by MCML Junior Member Mamdouh Aljoud and MCML Director Thomas Seidl, among others, won a runner-up prize at AutoML 2026.
27.10.2026
Welcoming Ewa Szczurek to MCML
Ewa Szczurek joins MCML as Professor of AI in Life Sciences at LMU, focusing on probabilistic and generative models for medicine.