In medicine, the documentation of patient cases and specialist knowledge generates large amounts of data. However, there is usually a lack of suitable solutions for the systematic exploitation of this data in practice. Artificial intelligence (AI) methods enable the efficient analysis and effective use of medical data. We conduct translational research on applied AI in clinical practice with a particular focus on radiation oncology.

Our research is based on the multimodal case data generated during the clinical patient journey, as well as the medical expertise used to carry it out. We use logical and probabilistic agents, various forms of machine learning, generative AI, concepts of explainable and ethical AI, and other methods from data science and decision-making. By equipping our AI solutions with suitable user-computer interfaces, we ensure a high level of usability. Our solutions address the analysis of patient cases, clinical treatment planning, patient empowerment, clinical quality management and other application scenarios.