AI at the Heart of Medicine - European Medical Journal

AI at the Heart of Medicine

Radiology
 

The EMJ Podcast | Episode 228

This week, Jonathan is joined by Chris McIntosh, to discuss the advancement of  AI from “bench-to-bedside”, while considering concerns around bias and fairness when working with diverse patient populations. 

Spotify | Apple | Amazon Music | YoutubeDownload MP3 (38 mins)

Speaker bio: 

Chris McIntosh Headshot

Chris McIntosh is a Scientist at Toronto General Hospital Research Institute, The Peter Munk Cardiac Centre, and The Joint Department of Medical Imaging, The University Health Network and Assistant Professor in the Department of Medical Biophysics, Computer Science, and Medical Imaging, University of Toronto, Toronto, Canada.

Having received his undergraduate degree and PhD from Simon Fraser University in Burnaby, Canada, McIntosh has gone on to become a renowned expert in medical image analysis and the clinical applications of AI. He has received numerous academic awards for his work, including those from the Natural Sciences and Engineering Research Council of Canada, the Canadian Institutes of Health Research, and the Michael Smith Foundation for Health Research.

McIntosh has worked with the GALEN group at the French national research institute for digital science and technology, INRIA in Saclay, France, and Ecole Centrale de Paris, and has worked as a research associate in the labs of Doctors Tom Purdie and David Jaffray. Now, Chris’s lab focuses on the theory and clinical application of AI in medicine, with the goal of improving patient care.

Timestamps:
  • 00:00 – Introduction
  • 02:28 – An early interest in computer science
  • 04:13 – Clinical collaborations
  • 07:46 – AI from “bench to bedside”
  • 10:08 – Transfer and meta-learning
  • 12:20 – Transparency in AI
  • 16:32 – Commercialising radiation therapy
  • 18:40 – AI revolutionising oncology
  • 20:49 – Treating cardiovascular disease
  • 25:45 – Bias in AI datasets
  • 31:47 – The future of AI
  • 35:00 – Chris’ three wishes for healthcare

Rate this content's potential impact on patient outcomes

Average rating / 5. Vote count:

No votes so far! Be the first to rate this content.

Thank you!

Please share some more information on the rating you have given