Success in medical AI isn't just about high accuracy; it's about building models that respect clinical constraints and address real-world needs
Nadia Vohwinkel
Nadia is dedicated to bridging the gap between clinical practice and computational science through interdisciplinary education. Currently, she is developing a framework that brings together students from medicine and machine learning to solve relevant problems in the field of medicine. By fostering a collaborative environment, Nadia focuses on the practical integration of ML solutions while encouraging critical reflection on the technical and ethical challenges inherent to both fields.
Success in medical AI isn't just about high accuracy; it's about building models that respect clinical constraints and address real-world needs