Jacqueline Ritter
Fraunhofer Institute for Manufacturing Engineering and Automation
Papers
1
Total Citations
17
H-Index
1
About
Jacqueline Ritter is a leading researcher at the intersection of artificial intelligence and cardiovascular medicine, specializing in autonomous robotic endovascular navigation. Her work focuses on developing recurrent neural network architectures that enable guidewires to generalize across varying vessel geometries, a critical step toward fully autonomous catheterization procedures. Ritter’s most cited work (2023, 17 citations) demonstrates how deep learning models can adapt to the complex, patient-specific anatomy of the aortic arch, addressing a key barrier to clinical translation. This research has immediate implications for improving physician ergonomics and expanding access to life-saving stroke and heart attack treatments in remote or underserved regions. Beyond this flagship study, Ritter’s contributions are shaping the emerging field of intelligent surgical robotics, where her algorithms bridge the gap between simulation-trained models and real-world anatomical variability. Her work is increasingly recognized for its potential to reduce procedure times and complication rates, positioning her as a rising voice in medical AI. Ritter’s research not only advances technical frontiers but also reimagines the future of minimally invasive care—making complex interventions safer, more consistent, and universally accessible.
Research Focus
Key Achievements
Top Papers
- 1