Revolutionizing Healthcare - Core Concepts: ML for Treatment Effects
van der Schaar Lab van der Schaar Lab
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 Published On May 22, 2024

Recording of the van der Schaar Lab's thirty-fifth Revolutionizing Healthcare engagement session for clinicians which took place virtually on 21 May, 2024.

The session was led by Tim Schubert and Tim Oosterlinck, two visiting medical students at the van der Schaar Lab who were guiding the conversation.

Treatment effect estimation helps to quantify the impact of specific medical interventions on patient outcomes - crucial information for improving clinical decision-making. By leveraging patient data, Machine Learning can predict outcomes with a precision previously unattainable. This technology is poised to not only forecast individual responses to treatments but also assist in developing new therapeutic strategies that are more effective. This allows healthcare to move beyond one-size-fits-all solutions and toward personalised medicine.

For this episode, Prof Mihaela van der Schaar first introduced the basics of personalised therapeutics to our audience, explaining the role of AI and state-of-the-art approaches.

Then we moved on further introductory presentations by our panellist. That was followed by a panel discussion informed by questions from the audience.

We thank Prof Richard Peck (CCAIM/University of Liverpool), Prof Pierre Marquet (University Hospital Limoges), and Prof Jean-Baptiste Woillard (University Hospital Limoges) for their participation.

Introduction - 0:00​
Session Overview - 3:10
Personalised Therapeutics & the role of AI by Mihaela - 4:09
A clinical and regulatory perspective on causal ML by Pierre - 18:14
Bridging the Worlds of Pharmacometrics and ML by Jean-Baptiste - 24:36
Industry Perspective by Richard - 32:01
Panel Discussion and Audience questions - 43:54
Intro to next sessions - 59:25

NOTE: This information was up-to-date at the time of the presentation but does not take into account material published since then.

We highly recommend a recent perspective in Nature Medicine, co-authored by Mihaela, which goes into detail about causal ML for predicting treatment outcomes: https://www.nature.com/articles/s4159...

You can find an introduction to individualised treatment effect inference on our lab website: https://www.vanderschaar-lab.com/indi...
There, you can also find a blog in which Machine Learning meets Pharmacology to unlock new frontiers in personalised medicine: https://www.vanderschaar-lab.com/mach...

As practising clinician, you can sign up for our upcoming sessions: https://www.vanderschaar-lab.com/enga...

Are you passionate for ML and want to start your AI journey? We invite you to the world’s first summer school on AI and Machine Learning for Medicine that is tailored exclusively for medical professionals and students. Find out more and join us: https://www.vanderschaar-lab.com/camb...

The lab's publications are here: https://www.vanderschaar-lab.com/publ...

Mihaela van der Schaar on Twitter:   / mihaelavds  
Mihaela van der Schaar on LinkedIn:   / mihaela-van-der-schaar  

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