Research Blog
28.07.2026
Gaps in the Benchmark: Why Medical AI Fails in the Real World
MCML Research Insight – With Jiazhen Pan, Bailiang Jian, Niklas Bubeck, Christian Wachinger, Benedikt Wiestler, and Daniel Rückert
We’ve all seen the headlines: the latest Artificial Intelligence model has aced the US medical licensing exams, scoring higher than many human doctors. It sounds like the future of healthcare has …
21.07.2026
The Learning Rate Does More Than Set the Pace
MCML Research Insight – With Maria Matveev, Vit Fojtik, Gitta Kutyniok, and Johannes Maly
A neural network can fit its training examples in many different ways. The harder question is which of these possible solutions will continue to perform well on new data, and whether the choices made …
29.06.2026
Research Stay at Stanford University
Felix Dülmer – Funded by the MCML AI X-Change Program
From March to May 2026, I had the opportunity to spend three months as a visiting researcher at Stanford University, hosted by Prof. Jeremy Dahl and the Ultrasound Imaging and Instrumentation Lab. …
26.06.2026
Research Stay at National University of Singapore
Bailiang Jian – Funded by the MCML AI X-Change Program
During my academic visit to Singapore. I am happy to work with the MVI-Lab lead by Prof. Hongwei Bran Li. The group works on a wide range of topics in medical image analysis, including CT-PET imaging …
10.06.2026
How Should Researchers Report Their Use of LLMs?
MCML Research Insight – With Stefan Feuerriegel, Barbara Plank, Kerstin Forster, Dominique Geissler, Abdurahman Maarouf, Sebastian Maier
Large Language Models (LLMs) are increasingly becoming part of scientific research. They can generate text, analyze data, simulate participants, and support researchers in entirely new ways. But there …
2024-11-22 - Last modified: 2026-07-31