van der Schaar Lab

Revolutionizing Healthcare: AI and ML for early detection and diagnosis (2/2)

The van der Schaar Lab’s fourteenth Revolutionizing Healthcare engagement session for clinicians took place virtually on March 10, 2022.

This session was the second instalment in a double-header focusing on the absolutely crucial topic of early detection and diagnosis (ED&D).

At the start of the session, Mihaela and an international panel of three expert clinicians (representing a variety of backgrounds) explored how AI and machine learning can help transform early detection and diagnosis (ED&D).

Our panel for this session consisted of:
  • Alberto Vargas, MD (Chief Attending, Department of Radiology, Memorial Sloan Kettering Cancer Center)
  • Prof. Henk van Weert (Professor, General Practice & Family Medicine, Amsterdam UMC; Research programs in oncology and cardiovascular diseases)
  • Prof. Stephen Friend (Visiting Professor of Connected Medicine, University of Oxford; Chairman and co-founder, Sage Bionetworks and 4YouandMe)

Following the roundtable, Dr. Eoin McKinney (one of our lab’s clinical and academic collaborators) presented a newly-developed machine learning demonstrator specifically designed for ED&D.

Introduction – 0:00
Declaration of interests – 0:44
Session overview – 1:32
Introductory presentation by Mihaela – 4:51
Meet the roundtable panelists – 14:37
Roundtable topic 1: opportunities for machine learning in ED&D – 15:36
Roundtable topic 2: new sources of information for ED&D – 30:23
Roundtable topic 3: advice for the machine learning community – 35:12
Presentation and demonstration by Eoin McKinney – 41:48
Intro to next sessions and note on CPD credits – 1:12:17

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

A written companion piece on ED&D (for a clinical audience) can be found here.

Sign up for our upcoming sessions here.

Jeroen Berrevoets

Jeroen Berrevoets joined the van der Schaar Lab from the Vrije Universiteit Brussel (VUB). Prior to this, he analyzed traffic data at 4 of Belgium’s largest media outlets and performed structural dynamics analysis at BMW Group in Munich.

As a PhD student in the van der Schaar Lab, Jeroen plans to explore the potential of machine learning in aiding medical discovery, rather than simply applying it to non-obvious predictions. His main research interests involve using machine learning and causal inference to gain understanding of various diseases and medications.

Much of this draws from his firmly-held belief that, “while learning to predict, machine learning models captivate some of the underlying dynamics and structure of the problem. Exposing this structure in fields such as medicine, could prove groundbreaking for disease understanding, and consequentially drug discovery.”

Jeroen’s studentship is supported under the W. D. Armstrong Trust Fund. He will be supervised jointly by Mihaela van der Schaar and Dr. Eoin McKinney.