Artificial Intelligence and Precision Medicine
Artificial Intelligence for More Personalized Medicine
The “Artificial Intelligence and Precision Medicine” working group develops AI-based analytical tools to automatically evaluate large volumes of clinical data and make it usable for medical diagnosis and treatment. The focus is on the fields of oncology, radiology, and cardiology. The use of artificial intelligence is intended to identify complex data patterns, support diagnostic processes, and enable personalized treatment approaches.
Linking Data Intelligently
A key research approach involves linking different types of medical data to provide a more comprehensive picture of individual clinical presentations and disease progression. To this end, modern imaging data is combined with additional clinical information and OMICS-based biomarkers and analyzed using multiparametric predictive algorithms. The goal is to gain new insights that enable a more precise assessment of individual health statuses and lay the foundation for personalized diagnostic and therapeutic decisions.
The Digital Twin as a Research Goal
In close collaboration with Siemens Healthineers, the working group is developing a digital twin. This involves combining various data sources and AI-supported analytical methods to digitally model complex biological and medical relationships. In the future, such models are expected to help identify disease risks at an early stage, better predict individual disease progression, and tailor diagnostics and treatment more precisely to individual patients.
Project Management Office
Medical Center – University of Freiburg
Center for Diagnostic and
Therapeutic Radiology
Department of Radiology
Killianstr. 5a
79106 Freiburg im Breisgau
+49 761 270-39795
carmen.steinborn@uniklinik-freiburg.de
