17.12.2024
©TUM
Daniel Rückert Advances Stroke Diagnosis With AI Innovation
TUM News
MCML Director Daniel Rückert and his collaborators have achieved a groundbreaking milestone in medical AI. Their innovative model uses machine learning to precisely determine the timing of strokes based on CT imaging. This advancement is critical for improving stroke diagnosis and ensuring patients receive timely and effective treatment. By addressing a long-standing challenge in neurology, this research exemplifies the transformative potential of AI in healthcare.
«We believe that our model is so powerful because it not only assesses how dark the damaged region is, but also includes additional features from the scans, such as texture, and accounts for variations within the damaged areas and background.»
Daniel Rückert
MCML-Director
Related
21.05.2026
Björn Eskofier Featured in Heise Online
Björn Eskofier participated in the panel discussion “How Research Scientists Build Health AI” at the Digital Health Innovation Forum.
11.05.2026
Cordelia Schmid Featured in Süddeutsche Zeitung
Cordelia Schmid, a member of the MCML Advisory Board, was recently featured in Süddeutsche Zeitung for her work in computer vision and robotics.
08.05.2026
Right Answer, Wrong Reasoning - Is AI Thinking or Cheating?
Can AI cheat without us noticing? Our PI Barbara Plank and her team introduce a new detection method at ICLR 2026.
