Andreas BedorfOn 18 January, we had our 22nd Revolutionizing Healthcare session. In that session, we explored Machine Learning Interpretability: Making ML output useful and actionable for clinicians and researchers.
The session also introduced Andrew Rashbass as our new session lead along with Mihaela. The the former CEO of The Economist Group, Reuters and Euromoney Institutional Investor PLC, and now works closely with Mihaela and the van der Schaar Lab on a range of initiatives.
Wednesday’s session started with a short introduction to the year as well as machine learning interpretability by Mihaela. This was followed by an extensive round table discussion with our clinical experts.
Our guests were:
– Prof Eoin McKinney, MD (University lecturer in renal medicine at the University of Cambridge; Honorary consultant in nephrology and transplantation, Cambridge University Hospitals NHS Foundation Trust; Faculty member at the Cambridge Centre for AI in Medicine)
– Dr Shinjini Kundu, MD, PhD (Resident physician and research scientist, Department of Radiology, at Johns Hopkins Hospital; MIT Technology Review’s 35 under 35, Forbes 30 under 30; winner of Carnegie Science Award; her research focuses on developing new explainable AI technologies for medical diagnosis)
Afterwards, we invited questions from the audience and the session developed into an interesting discussion including the perspectives from a variety of clinicians.
If you would like to learn more about the topic, please have a look at our research pillar on the topic, as well as our previous Revolutionizing Healthcare sessions about interpretable ML from 31 March 2021 and 27 April 2021.
If you didn’t manage to join us last week, we’d strongly recommend watching the archived video, which is now available on YouTube:
NOTE: This information was up-to-date at the time of the presentation but does not take into account material published since then.
Sign up for our upcoming sessions here.
Tim Schubert
Tim Oosterlinck
Evgeny Saveliev
Mihaela van der Schaar
