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A Mutual Exchange Extending Beyond Individual Disciplines
These two closely related fields, artificial intelligence and medicine, thrive on dialogue, discourse, and collaboration that extends beyond one's own personal expertise, particularly between the various disciplines. The event intends to initiate and stimulate interdisciplinary interaction that mutually benefits both sides. We will focus on approaches to issues, current developments, the challenges facing theses interdisciplinary fields, and provide topics to support productive discussions.
Event: AI in Medicine
DATE
Wednesday, September 20, 2023
5:30 - 7:30 PM
A small reception and refreshments will follow.
LOCATION
YOU CAN EXPECT
A keynote address, discussions, networking opportunities
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Keynote Speech for: AI in Medicine
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Evangelia Christodoulou
German Cancer Research Center (DKFZ)
Post-doctoral fellowship as part of the AI Health Innovation Cluster, opens an external URL in a new window
Drawing on her educational background, Evangelia Christodoulou holds a BSc. in mathematics and an MSc. in Biostatistics. In 2021, she successfully completed her PhD in clinical prediction modelling at KU Leuven, Belgium, with guidance from Professor Ben Van Calster. Throughout her doctoral studies, she garnered valuable experience collaborating in an interdisciplinary setting that brought together oncologists and statisticians. Her contributions during this period were particularly impactful, concentrating on enhancing the methodological integrity and validation procedures for predictive algorithms utilizing clinical data.
In February 2021, she became a member of the German Cancer Research Center (DKFZ), securing a postdoctoral fellowship as part of the AI Health Innovation Cluster of the department led by Professor Lena Maier-Hein. At present, her research focuses primarily on validating AI algorithms in the realm of medical imaging analysis. Furthermore, she is delving into the potential of deep learning techniques to support clinical prediction utilizing tabular data.
![[Translate to Englisch:] Portrait der Vortragenden](/fileadmin/_processed_/e/8/csm_Christodoulou_Portrait_3c50702c9f.jpeg)
©Christodoulou
AI in Medical Imaging Analysis: Successes, Caveats, and How to Move Forward
AI algorithms have the potential to reshape the landscape of healthcare. Recent achievements of AI models in the medical field, combined with the intrigue surrounding Large Language Models (LLM) such as chatGPT, Llama 2, and the like, introduce certain considerations from both medical and ethical standpoints.
This naturally gives rise to a fundamental question: To what extent can we place our confidence in modern AI algorithms to aid in patient management, and how can we navigate this terrain safely? During my presentation, I will predominantly delve into subjects related to validating AI algorithms as part of the sphere of medical imaging analysis. This will lay the foundation for discourse related to the measures necessary to establish reliable AI applications in the medical domain.
