News

Video

ASRS Live: Aaron Lee, MD, shares updates on deep learning research

At the 2023 ASRS meeting in Seattle, Washington, Aaron Lee, MD, spoke with our team about his research and how changes are making new training possible. He shared how research and new techniques are expanding the options for deep learning in ophthalmology.

Aaron Lee, MD, shared how research and new techniques are expanding the options for deep learning in ophthalmology. At the 2023 ASRS meeting in Seattle, Washington he spoke more about his research and how changes are making new training possible.

Video Transcript

Editor's note - This transcript has been edited for clarity.

Aaron Lee, MD:

Okay, I'm Aaron Lee. I'm at the University of Washington. I'm an associate professor there. My research for the last couple of years has really been on the focus of artificial intelligence and big data, and trying to understand and uncover new associations in opthalmic diseases using these very powerful techniques. But the, one of the critical ingredients that has been really missing in our field has been the availability of large datasets, large imaging datasets, in particular, that you need to train these very large, deep learning models.


And so the presentation I'm giving is really about how to build the next future of large datasets that everybody can use to train deep learning models, in the field of ophthalmology. One of the things that's really important for this is the standardization of those images so that it's easy for researchers to use.
Traditionally, those images have always been sort of locked up in a way that it makes it very difficult for people to open, but actually Heidelberg, with the Heyex PACS system allowed for those images to be unlocked in a way where you can just literally copy them off the hard drive and open them in a third party viewer.

And because Heidelberg made this move, the whole industry now is moving in this direction. And it's really sort of transforming the landscape of the availability of this kind of data. So we're very, sort of excited, about the new future of data science in retina research in particular. And so that's really sort of the focus of my research and what we're doing for the next couple of years.

Related Videos
Eye stroke: Mount Sinai program stresses awareness and emergent care for sudden vision loss
What the re:Vive 2.0 platform may mean for the future of vision diagnostics
Deep learning analysis detects diabetic retinopathy on ultra-widefield scanning laser ophthalmoscope images
Exploring ancillary testing orders by retinal specialists according to the IRIS registry
© 2024 MJH Life Sciences

All rights reserved.