Driven by a medical need and with direct access to the medical infrastructure, the EKFZ accelerates digitization in medicine for the benefit of the patient.
Scientific Focus
The Else Kröner Fresenius Center (EKFZ) for Digital Health, is a joint cross-faculty initiative of the Technische Universität Dresden (TUD), the University Hospital Carl Gustav Carus Dresden (UHD) along with several Fraunhofer and Helmholtz institutes on the Dresden campus. Whereas conventionally the School of Medicine and the high-tech specialists work and research independently, the EKFZ bundles their expertise and brings them together through its interdisciplinary structure and network. Driven by a medical need and with direct access to the medical infrastructure, the EKFZ accelerates digitization in medicine for the benefit of the patient.
The EKFZ focuses its research effort on the direct interface of the digital world to the patient thereby serving as a bridge between medical big data efforts and traditional biomedical engineering. The EKFZ is structured in virtual application rooms that represent strategic development areas and will be strengthened by specific appointments for center professorships, and in core rooms, which provide the scientific infrastructure and theoretical basics. The competences from the core rooms are the basis for successful translation of high-tech innovation into routine care.
Application rooms
Digitization offers a variety of new approaches for personalized medicine and AI-based diagnostic recommendations. In particular, the chair will contribute to deepening the connection between medicine and computer science at TU Dresden to further develop the field of clinical use of artificial intelligence methods. The Faculty of Medicine and the Faculty of Computer Science will be linked with the EKFZ in a central role in research, teaching and transfer in order to deepen the connection between medicine and computer science at TU Dresden.
The application room aims at addressing tangible, clinically relevant questions using artificial intelligence methods of the following topics: developing AI-based clinical recommendations for action and therapy support systems, exploiting the linkage of molecular, clinical and imaging data or gaining new insights into the pathomechanisms of diseases.
The future workplace for healthcare professionals will command much more data and offer inherent intelligence and assistance. In order for this workplace to function properly, healthcare professionals and supporting technology must interact privately, safely and conveniently. New spaces of information delivery arise, be it surgical theatres, hospital rooms or medical homecare environments. In order to enable these spaces to become “smart”, more and more real time sensory data need to be set to context and be interpreted by algorithms driving automated processes or by patients and healthcare professionals.
At the bedside, devices such as laptops or tablets are of limited use due to hygienic requirements and the need for a high degree of interaction flexibility with the patient. Here it is necessary to develop mobile assistance (and communication) systems based on augmented reality technologies, which are able to capture and process situations and contexts on the basis of static information and relevant sensor data and to provide multi-professional user groups with relevant data according to their needs. As a rule, these assistance solutions must not interfere with the human interaction with the patient, so that an intelligent control logic must be developed for this purpose, which takes into account the special requirements and the context of medical professionals. These are the main research agendas of the application room Connected care.
Implants, Sensors and Devices epitomize the concept of bringing digital health to the patient interface, as data is obtained closely to the pathophysiological process. So far, sensors and diagnostics reside often outside the body. Here we are moving closer to the patient in selected application areas, as research is specializing in sensors and applications close to or inside the patient’s body, such as implantable sensors or personalized implants. The respective professorship will serve as a central facilitator for medical sensor and implant activities and will perform teaching courses for engineers and future physicians.