AIC: Artificial Intelligence - Key to Next Generation Healthcare?

Donnerstag, 03.03.2022, 16.00 Uhr

Im November 2021 startete eine neue Veranstaltungsreihe des RWTH KI-Centers: das “Artificial Intelligence Colloquium”, kurz AIC. Hier präsentieren renommierte Wissenschaftler der RWTH und anderer Universitäten hochaktuelle Forschung zu Methoden und Anwendungen der Künstlichen Intelligenz. 

  Andreas Schuppert

Driven by great progress in deep learning and availability of large biomedical data sets, promising studies suggest artificial intelligence to be a key technology in order to realize a quantum leap towards next generation medicine and public health. However, implementation remains behind expectations because of unsolved conceptual computational challenges playing a key role both in clinical applications as well as in public health. On the example of the dynamics of Covid19 spreading Prof. Andreas Schuppert will show the role of self-adaptive closed-loop control in combination with missing data in health care systems. Insufficient observability in combination with a lack of mechanistic understanding of the underlying mechanism of self-adaptability significantly hamper efficient modelling with acceptable prognostic precision. Conceptual routes towards prognostic modelling in self-adapting, closed-loop control systems on the example of learning the mechanisms of control of covid19 infection waves will be discussed.

Andreas Schuppert is Professor for Computational Biomedicine and founding director of the Joint Research Center for Computational Biomedicine at RWTH Aachen University. He studied Physics and got a PhD in mathematics from University Stuttgart, followed by research and development positions in chemical-pharmaceutical industry. In 2007 he became Adjunct Professor at RWTH Aachen, where he became founding director of the Joint Research Center for Computational Biomedicine in 2013, a private-public partnership between RWTH Aachen University Hospital Aachen and Bayer AG. Since 2017 he is head of the Institute for Computational Biomedicine.
His focus is on research and development of hybrid modelling technologies with focus on applications in intensive care, oncology, pain research. During the Covid19 pandemics he developed the DIVI prognosis tool and focused on pattern recognition in pandemic dynamics.



Das AIC richtet sich vor allem an Forschende und Masterstudierende und wird bis auf Weiteres virtuell stattfinden. Eine Anmeldung ist erforderlich, um die Einwahldaten für das Zoom-Meeting zu erhalten.

RWTH Intern