Knowledge- and data-driven personalization of medicine at the point of care

Due to the increasing digitalisation in medicine, more and more data is becoming available. Yet, the challenge is to make the knowledge contained in this data available and usable at the point of care, especially, when making therapy decisions. Existing clinical information systems facilitate the collection and storage of important information, but usually in a relatively unstructured manner and without an individual, context-related compilation of the facts relevant to a treatment decision. The aim of the Research Training Group is enabling young researchers to obtain a holistic overview of the current state of research on knowledge- and data-based personalization of medical decision-making processes. They shall design new interdisciplinary methods and implement them as prototypically using the example of malignant melanoma. For this purpose, methods from the fields of information extraction, knowledge representation with machine learning methods and user interaction at the point of care are combined in a novel way.

Institute for AI in Medicine (IKIM)