In modern medicine, and especially in the field of radiological imaging, huge quantities of data are produced – so much that medical diagnosis of the images poses an increasingly time- and labor-intensive challenge. The utilization of artificial intelligence (AI) promises a major potential here in achieving synergetic effects: Activities that are carried out best by AI algorithms can be combined with those best suited for medical professionals. Within the scope of the Else Kröner Clinician Scientist Professorship, AI is used to develop new kinds of solution approaches to enable improved radiological diagnostics and therapy management. The research activities concentrate particularly on pathologies from the diagnostic spectrum of neuroradiology – the focus is placed above all on brain tumors and strokes. The methodological emphases lie in establishing continuously learning, multicentrically validated and interpretable AI models, because they are going to have a central role for the successful translation of clinically applicable AI in radiology.
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