About us: Research group “Clinical Artificial Intelligence

We are a young, interdisciplinary group of scientists using computational methods to extract actionable knowledge from clinical routine data. Our main tools are Artificial Intelligence and Computational Modeling. We combine these tools with a clinical perspective on health and disease. Our main strength is precision oncology of solid tumors and we are interested in cancer genomics, targeted treatment and immunotherapy. To learn more about our research, have a look at our featured publications.

Our affiliations

Until end of May 2022, we are based at RWTH University Hospital in Aachen, Germany. In June 2022, the lab will be moving to the Else Kroener Fresenius Center for Digital Health at Technical University Dresden. In addition, we are and remain affilated with the Department of Medical Oncology, National Center for Tumor Diseases, Heidelberg, Germany and the Department of Pathology and Data Analytics, University of Leeds, Leeds, UK.

Our funding

We received and are receiving funding by RWTH Aachen University (“START” program), the Academy of Sciences and Arts of the state of North-Rhine Westphalia (“Junges Kolleg”), by the German Cancer Aid (Deutsche Krebshilfe, “Max Eder research group”), by the German Federal Ministry of Health (BMG, “DEEP LIVER”), the German Federal Ministry of Education and Research (BMBF, “PEARL”) and the Innovation Fund of the “Gemeinsamer Bundesausschuss” (G-BA, “Transplant.KI”).

Sustainability

Planetary health is a prerequisite for individual health. For us as scientists and clinicians, it is imperative to spread awareness: we need to limit global temperature increase and restore biodiversity to protect health.

Recent Posts

Our lab is moving to Dresden

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Towards targeted treatment of cancer with Artificial Intelligence

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Survey on AI applications in pathology

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Our research featured in the news

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How to develop AI biomarkers for the clinic

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New job opportunity in our group

Our research featured in the news

Large international consortium for deep learning-based genotyping of colorectal cancer: MSIDETECT

New publication: Pan-cancer image-based detection of clinically actionable genetic alterations

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