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
19.01.2026
MCML at AAAI 2026
MCML researchers are represented with 11 papers at AAAI 2026 (8 Main, and 3 Workshops).
19.01.2026
MCML PI Frauke Kreuter Featured on ARD Alpha on AI
MCML PI Frauke Kreuter featured on ARD alpha discussing AI in daily life, workplace applications, and responsible, future-ready use.
15.01.2026
Blind Matching – Aligning Images and Text Without Training or Labels
CVPR 2025 research from Daniel Cremers’ group shows how images and text can be aligned without training data, labels, or paired examples.
12.01.2026
MCML PIs Featured in Süddeutsche Zeitung
MCML PIs Xiaoxiang Zhu and Felix Dietrich featured in Süddeutsche Zeitung for TU Munich’s 2025 breakthroughs in AI and data science.