Louis Pasquale, MD: Evolution of Technology in Ophthalmology


Louis Pasquale, MD, professor of medicine at Icahn School of Medicine at Mount Sinai, discusses how technology and artificial intelligence has impacted ophthalmology.

As healthcare and technology advance and become increasingly intertwined, there is an onus across every specialty and field of medicine to tread a careful line of implementing artificial intelligence in a way that benefits both patients and clinicians.

In no field does this ring more true than in ophthalmology. With blindness among the greatest healthcare concerns of virtually every patient population, using artificial intelligence and machine learning in a way that streamlines practice while helping patients sustain their vision is the primary focus of many in the field.

A clear testament to this was the subject matter of presentations, posters, and papers at the American Academy of Ophthalmology (AAO) 2019 Annual Meeting in San Francisco, which featured more than 2 dozen pieces of research centered around artificial intelligence. What was once an idea met with skepticism has carved its own niche in the field.

For Louis Pasquale, professor of medicine at Icahn School of Medicine at Mount Sinai, the continual advancement of artificial intelligence is one of the most exciting aspects of ophthalmology. A co-investigator on multiple pieces of research assessing use of artificial intelligence and machine learning algorithms, Pasquale’s perspective as an educator, researcher, and practicing physician give him a unique vantage point on the topic.

To learn more about how technology has advanced and impacted ophthalmology, MD Magazine® sat down with Pasquale between sessions at AAO 2019 to hear his opinion.

MD Mag: How has the onset of AI and machine learning in medicine impact ophthalmology?

Pasquale: Ophthalmology is an amazing field that's always been on the cutting edge of new technologies. I mean if you take a quick snapshot through time, one of the things that got me interested in ophthalmology in the first place is they were among the first people to use an operating microscope.

Ophthalmology was the discovery of the first tumor suppressor gene in retinal blastoma. With one of the more recent revolutions in genomics, one of the first genes discovered in genomics was complement factor H from macular degeneration and now we're seeing a new revolution in AI and ophthalmology is really on the forefront of that—it's interesting. Dr. Eric Topol, who is an expert in big data, he's a cardiologist here in California has, himself, stated that ophthalmology is really on the cutting edge of artificial intelligence.

What can artificial intelligence do for ophthalmology? Many things. I'm a glaucoma specialist and, in our field, there are many gaps in glaucoma care. If you put five experts in a room and you showed them images of an optic nerve, there would be considerable disagreement about whether or not that optic nerve constitutes glaucoma—this damage or not. It's kind of surprising that that's the case, but it's true. In the realm of visual field testing, we would love to have an algorithm that could objectively detect visual field progression and what we're seeing outside of glaucoma is explosions in the area of artificial intelligence.

Recently the FDA approved IDX, which is an autonomous algorithm for detecting referral diabetic retinopathy, and now you've seen an explosion around the world using that method or related AI algorithms to detect diabetic retinopathy, which is really critical because we have an epidemic, so to speak, of diabetes and we have a relative lack of manpower to identify patients who might have diabetic retinopathy and need treatment and we all know that diabetic retinopathy is a treatable disease.

So, the sky is the limit about what AI could do next in my field. It would be wonderful if AI could predict—and I think that it could predict—which patients are going to be rapid progressers, which patients might need surgery, what would be an appropriate target intraocular pressure for treatment of the disease, etc. So, there's tremendous amount that I believe AI still can do in our field.

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