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Due to the increasing digitization in medicine, ever more data is being generated and made available, for example in electronic patient records, laboratory analyses or clinical guidelines. It is a challenge to make the knowledge contained in these different classes of data available and usable at the PoC for concrete individual therapy decisions. Existing clinical information systems allow the collection and storage of important information, but relatively unstructured and without individual, context-related compilation of the relevant facts for treatment decisions. 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 can gain a holistic overview of the state of research on knowledge- and data-based personalisation of medical decision-making processes and learn to design new interdisciplinary methods, as well as implement prototypes such as malignant melanoma. In novel ways, methods from the fields of information extraction, knowledge representation are combined with machine learning methods and findings on user interaction at the PoC. Interdisciplinary measures, in particular hospitations at the dermatological clinic, will reduce the barriers of understanding between these disciplines. A unique characteristic of the Research Training Group is the inter-institutional cooperation between the University of Applied Sciences Dortmund, the University Duisburg-Essen and the University Medicine Essen. This is based on an already existing cooperation through a joint study course Medical Informatics. The applicants represent a broad range of expertise in the fields of medical informatics, bioinformatics, epidemiology, artificial intelligence, psychology, radiology and melanoma research. Graduates of our program will be able to assume leading roles in the digitization process of the health care system and to further improve treatment methods with the help of artificial intelligence methods, taking into account the direct feedback and experience of the attending physicians.