Digital Twins for Surgery - With Researcher Azade Farshad

Azade Farshad, MCML Junior Member and PhD student in the research group of Nassir Navab, researches digital twins of patients at TUM and MCML to improve personalized treatment, surgical planning, and training. Using graph-based analysis and multimodal patient data, she builds models that create realistic surgical simulations — helping surgeons preview procedures, spot potential complications, and optimize strategies.

Think of it like using a detailed, interactive 3D map before a complex road trip — but for surgery.

Watch the video and learn how AI can improve personalized treatment for patients. This video is part of the project KI Trans, an initiative in collaboration with TüftelLab and Uta Hauck-Thum from Ludwig-Maximilians-Universität München, focused on equipping teachers with the essential skills to navigate AI in schools. The project is funded by the Bundesministerium für Forschung, Technologie und Raumfahrt as part of DATIpilot.