The Federal Ministry of Research, Technology and Space has approved the application and subsequent funding for the TRANSFER project, led by ECDF members Felix Balzer, David Bermbach and Elias Grünewald. 

The aim of the project is to use artificial intelligence (AI) to predict phases of low blood pressure (hypotension) and restricted blood flow (hypoperfusion) during anesthesia for non-cardiac surgery at an early stage – thereby supporting anesthesiologists in real time. The goal is to reduce serious post-operative complications such as heart attacks or kidney failures, and thus contribute to lowering mortality, complications, and treatment costs.

At its core is a data platform that processes sensor data in a fail-safe, reliable, and near real-time manner. It serves as a runtime environment for AI modules, enabling their further development and the traceability of recommendations. Modern technologies from cloud native, big data and stream processing are being evaluated for the TRANSFER use case.

The project is being carried out in cooperation with ID Information und Dokumentation im Gesundheitswesen GmbH & Co. KGaA, SectorCon Ingenieurgesellschaft mbH, Charité Universitätsmedizin Berlin, and DFKI. It is funded by the German Federal Ministry of Research, Technology and Space for a duration of three years (01.06.2025 - 31.05.2028).