AI & medicine: safe systems and their certification

Carl Zeiss Foundation funds research project with five million euros

Modern deep-learning systems in healthcare have the potential to make diagnostic decisions of similar quality to treating physicians. However, there are concerns about the transparency, robustness, fairness and reliability of these systems. The project “Certification and Foundations of Safe Machine Learning Systems in Healthcare” by a research group at the University of Tübingen aims to address these issues. Potential trade-offs of various aspects (fairness, accuracy, interpretability, and privacy) as well as their ethical implications are being explored using concrete applications in the healthcare sector. The Carl Zeiss Foundation is now funding the project as part of its “Scientific Breakthroughs in Artificial Intelligence” program with five million euros over six years.

Thumb ticker sm prof hein mpi52
University of Tübingen
Thumb ticker sm img 7595
University of Tübingen
Thumb ticker sm cb1
University of Tübingen
Thumb ticker sm philipp cropped small
University of Tübingen
Thumb ticker sm thumb ticker md mackejakob012
University of Tübingen
Thumb ticker sm bethge matthias
University of Tübingen
Thumb ticker sm profile color
ELLIS Institute Tübingen, Max Planck Institute for Intelligent Systems & Tübingen Al Center
Thumb ticker sm csm nicocutnewbackground 70da50bef5
University of Tübingen
Thumb ticker sm profilesquare
Max Planck Institute for Intelligent Systems

Related Articles

Thumb ticker md cyber valley x start ups 4

The Cyber Valley Start-up Network continues to grow

Medicalvalues, NECKAR, Yugen Space, and Tetractys join the Cyber Valley Community
Arrow left
Thumb ticker md design learnings graphics and comments 12

IMPRS-IS Call for Applications is Now Open

Join the Cyber Valley Community as a PhD student
Arrow left
Thumb ticker md cyber valley x start ups 2

Cyber Valley welcomes four start-ups to the Start-up Netw...

Enriching the Cyber Valley Community
Arrow left