From Physics Based Simulation to AI Driven Models of Stent Frames for Transcatheter Valve Replacement
The goal of this presentation is to show how simulation workflows can generate sufficient training data for an AI system that rapidly predicts the deformation of transcatheter aortic valve replacements. Two examples will illustrate how SimAI can support the stent-frame design process, enabling faster evaluation of design variants. A third example will focus on a clinical use case, demonstrating how rapid deployment predictions could provide valuable insights during a surgical procedure. Altogether, this approach allows design engineers to quickly assess concepts under realistic loading conditions and streamline both development and clinical decision‑making.
