Certification and Foundations of SafeMachine Learning Systems in Healthcare
| Focus topic: | Artificial Intelligence |
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| Type of funding: | Project funding programmes |
| Programme: | CZS Breakthroughs |
| Funded institution: |
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An interdisciplinary team at the University of Tübingen is exploring principles for the safe use of AI systems in healthcare and developing guidelines for their certification.
Goals
Modern Deep Learning systems in healthcare have the potential to make diagnostic decisions of similar quality to attending doctors. However, there are concerns about their transparency, robustness, fairness, and reliability. The goal of this project is to address these issues by exploring the interdependencies and potential trade-offs of different aspects (fairness, accuracy, interpretability, and privacy) as well as their ethical implications in concrete healthcare applications. The aim is to establish guidelines for the certification of such systems and thus enable their safe use in medicine.
Involved persons:
Prof. Dr. Matthias Hein
Eberhard Karls Universität Tübingen
Detailed information:
| Focus topic: | Artificial Intelligence |
|---|---|
| Programme: | CZS Breakthroughs |
| Type of funding: | Project funding programmes |
| Target group: | Professors |
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| Funding budget: | 5.000.000 € |
| Period of time: | Februar 2022 - Januar 2028 |
Funded institution:
