University Medical Center Göttingen
Founded in the year 1737, the Faculty of Medicine has been combined with the University Hospital as part of a so-called “integration model”. With approximately 120 professors and around 3100 students in the fundamental study programmes, UMG is occupying a leading position nationwide, particularly focussing on the research areas of neuroscience, cardiovascular research and oncology. Together with the German Centre for Neurodegenerative Disease (DZNE), the Biology and Natural Sciences Departments, as well as eight non-university local research centres – such as the Max-Planck Institutes and the German Primate Center (DPZ) - UMG is embedded in the scientific world-class hub of the Göttingen Campus, having initiated or being engaged in a high number of high-quality international projects and collaborative activities of multidisciplinary nature. With ample experience in transnational and multi-beneficiary research projects as well as numerous training programs, UMG is used to translate basic research into clinical applications. As a Neuromuscular Centre certified by the DGM e.V. in Germany, UMG is member of the European Reference Network (ERN) for NMD, member of CORD-MII and member of the HiGHmed consortium of the Medical Informatics Initiative. Having established a medical data integration center (MeDIC), that implements the FAIR guiding principles for healthcare data, UMG is integrated across multiple entities and sites. UMG has set up a Clinical Trials Center and hosts several research infrastructures for large inter-institutional research collaborations, such as the German Center for Cardiovascular research (DZHK)
Role within Screen4Care
Within Screen4Care, UMG provides clinical disease data, biomaterial & the methods for morphological analysis combined with modern imaging approaches, clinical pilot on EHR & guides the interaction between CORD-MII & NM Centres. UMG will also offer guest lectures, university events (e.g. science night or public lectures, if applicable), and seminars to promote the contents of genetic NBS and ML-based diagnostic approaches, including the limitations and required improvements.
