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Robustness in Healthcare AI - A Deep Dive

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Robustness in Healthcare AI - A Deep Dive

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We. Are. Back!

Join us for our next Machine Learning in Healthcare meetup in Berlin, sponsored by the QUEST Centre!

In this event, we will explore the concept of Robustness in Healthcare AI, with two expert speakers.

Talk 1, Valerie Bürger, "Understanding Robustness in AI: Theoretical Insights and Practical Challenges"

Meta-research—the study of research itself—defines robustness in AI as a combination of reliability and validity. Reliability ensures that findings remain consistent despite variations in data and analysis, while validity tests whether results hold up across different experimental setups and contexts. This broader perspective on robustness is particularly critical for AI applications in healthcare, where models must consistently perform well in diverse real-world settings. Despite its importance, the AI field lacks mature processes and practices to systematically ensure robustness, leading to a fragmented understanding of the concept. In this talk, Valerie will explore various definitions of robustness and provide insights into its theoretical and scientific dimensions within AI.

Valerie is a psychologist, ethicist, and PhD candidate specializing in mental health AI. Passionate about the intersection of technology and ethics, her research aims to advance responsible and effective AI applications. With a strong interdisciplinary focus, she is eager to engage in discussions spanning the philosophy of technology to the concrete clinical implementation of AI tools.

Talk 2, David Higgins, "The Builder’s Journey".

Building an AI-containing medical product is complicated. Drawing on work from his peer-reviewed articles, David will present the entire journey in bite-sized chunks from Macro to Micro and back again. And he says: In the end everything is about robustness!

David is a mathematician and computer scientist with a Ph.D. in computational neuroscience from the École Normale Supérieure. Since late-2017, he has split his time between academia and the health-tech industry. A founder of two start-ups, one in pharma R&D and the other delivering behavioural change therapy to patients. David is well-known for advancing ML best-practices in healthcare. He is a mentor to many AI-driven health-tech spin-outs from major institutions across Europe and the US.

We will meet - as usually - in the “Atrium” conference room of the BIH, 5th floor of the Spreepalais, Anna-Louisa-Karsch-Straße 2, 10178 Berlin. Please enter the lobby, find the elevator group at Aufgang A and get out on the 5th floor. The entrance to the meeting room is labeled.
We will of course provide food and drinks!

Please, if your RSVP-ed but realize that you can´t join please make sure to make your spot available for someone else!

Be aware that sometimes only one of the 4 elevators works!

The venue and food/drinks are kindly provided by the QUEST Center

Doors will be open at 6 pm, we will begin at 7 pm sharp.

6-7 pm: arrival, food, and networking
7 pm: Introduction by the hosts.
7:03 pm: talk Valerie + Q&A
8 pm: talk David + Q&A
9 pm: networking

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Machine Learning in Healthcare Berlin
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Berlin Institute of Health (BIH)
Anna-Louisa-Karsch-Straße 2, 10178 · Berlin