About the RTG
GoalsOur intention and vision
Thanks to increasing digitization in medicine, more and more data is becoming available, for example in electronic patient records, through laboratory analyses, or even in treatment guidelines. One challenge is to make the knowledge contained in this very diverse data available and usable at the point of treatment for concrete individual therapy decisions. Existing clinical information systems allow the collection and storage of important information, but usually in a relatively unstructured way and without an individual, context-related compilation of the facts relevant for a treatment decision. The aim of the research training group is to train young researchers from the fields of medical informatics, computer science, statistics, epidemiology, and psychology so that they obtain a holistic overview of the state of research on knowledge- and data-based personalization of medical decision-making processes and learn to design new methods on an interdisciplinary basis and implement them prototypically using the example of malignant melanoma. For this purpose, methods from the fields of information extraction, knowledge representation with machine learning methods, and insights into user interaction at the point of care will be combined in a novel way. Through interdisciplinary measures, in particular through job shadowing in the dermatology clinic, barriers to understanding between the disciplines are broken down. Unique for a research training group is the cross-institutional cooperation between the Dortmund University of Applied Sciences and Arts, the University of Duisburg-Essen, and the University Hospital Essen, which is based on an already existing cooperation through a joint study program in medical informatics. Together, the applicants represent broad expertise in the fields of medical informatics, bioinformatics, epidemiology, artificial intelligence, psychology, radiology, and melanoma research. Graduates of our program will be able to take leading roles in the digitization process of healthcare and further improve treatment pathways using artificial intelligence techniques, taking into account the direct feedback and experience of the treating physicians.