Revolutionizing Healthcare: Concrete steps for clinicians to make machine learning a reality in a clinical setting

On 16 February, we had our 23rd Revolutionizing Healthcare session. In that session, we explored concrete steps for clinicians to make machine learning a reality in a clinical setting.

The session started with an introduction to Revolutionizing Healthcare and the significance of taking action by Prof Mihaela van der Schaar. This was followed by two highly relevant presentations by and for practicing clinicians, as well as an extensive round table discussion with our clinical experts.

Our guests were:

Dr Tom Callender, MSc MRCP, a public health doctor and a regular in our sessions who uses machine learning in his work, delivered a concise tutorial on the concrete steps a clinician can take to get up and running with ML.

Part of his work revolves around AutoPrognosis, the van der Schaar Lab’s newest framework offering the healthcare community a tool that utilises the power of AutoML in a flexible, accessible, and interpretable way.

Professor Brent Ershoff, MD, Assistant Professor at UCLA, presented a case study about applying machine learning to relatively small amounts of proprietary data collected in his hospital in order to better manage operating-room resources. 

The tutorial and the case study covered real-world, practical, clinical and operational use cases. We hope that the session inspires and helps you to start planning how you will introduce machine learning into your practice. We are looking forward to welcoming you tomorrow.

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.