17.12.2024
©TUM
Daniel Rückert Advances Stroke Diagnosis With AI Innovation
TUM News Article
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
17.12.2024
Related
©Florian Generotzky / LMU
01.04.2025
AI as Co-Pilot
AI tools by Stefan Feuerriegel’s team at LMU support public decision-making, aiming for efficiency, transparency, and human control.
©Astrid Eckert / TUM
31.03.2025
Robot Jack Navigates Like a Human – A Project Led by Angela Schoellig
Angela Schoellig’s team at TUM developed robot Jack, which navigates safely through crowds using human-inspired motion planning.
©TUM
18.03.2025
New Method Significantly Reduces AI Energy Consumption
Felix Dietrich and his team at TUM developed a new method that significantly reduces AI energy consumption, making AI more efficient and sustainable.
10.03.2025
Björn Schuller Was Featured on ARTE TV
Björn Schuller was featured in an ARTE TV documentary on AI therapy, presenting his research on emotion recognition.
