Revolutionizing Healthcare was established by Prof Mihaela van der Schaar in September 2020. Since then, we have had more than twenty intriguing, thought-provoking, and engaging sessions.
What? Revolutionizing Healthcare is a series of engagement sessions for clinicians, aiming to share ideas and discuss topics that will define the future of machine learning in healthcare. These events are for members of the healthcare community and focus on challenges and opportunities in clinical application of machine learning. We now have over 650 clinicians from around the world registered to participate in these sessions.
Why? As a lab, our purpose is to create new and powerful machine learning techniques and methods that can revolutionise healthcare. This doesn’t happen in a vacuum. At inception, we are inspired by ideas and discussions; in implementation, we need connections, trust, and partnership to make a real difference.
Who? While you can learn about our work at major conferences in machine learning or in our papers, we think it’s a better idea to create a community and keep these conversations going. We’re also aware that many people—both in healthcare and machine learning—have questions about what we do, and how they can contribute. We have chosen to restrict access to the actual discussion in the Revolutionizing Healthcare sessions to practicing clinicians so that we can maintain a focus on the clinical issues.
We also have dedicated engagement sessions for ML researchers and practitioners called Inspiration Exchange, which focuses on the development of new methods, approaches and techniques.
Next session on 8 December!
Our next session will take place on 8 December. In this, our 30th jubilee session, we will explore Large Language Models!
If you’d like to join us for this or future sessions, please sign up using the form below, and check this page regularly.
Cambridge, United Kingdom Tue, 08 December 2023 at 16:00 GMT
Paris, France Tue, 08 December 2023 at 17:00 CET
New York, USA Tue, 08 December 2023 at 11:00 EST
San Francisco, USA Tue, 08 December 2023 at 08:00 PST
Beijing, China Tue, 08 December at 00:00 CST
More time zones can be found here.