Using Artificial Intelligence to Diagnose Glaucoma
In This Video
- David S. Friedman, MD, PhD, MPH, is a clinician scientist and director of the Glaucoma Service at Mass Eye and Ear/Massachusetts General Hospital Department of Ophthalmology and professor of Ophthalmology at Harvard Medical School
- Dr. Friedman discusses the implementation of artificial intelligence in the detection of glaucoma in screening with photographs
- The technology, which can also detect diseases like diabetic retinopathy or macular degeneration, directly analyzes the photo and determines the likelihood of glaucoma being present
David S. Friedman, MD, PhD, MPH, is a clinician scientist and director of the Glaucoma Service at Mass Eye and Ear/Massachusetts General Hospital Department of Ophthalmology and professor of Ophthalmology at Harvard Medical School. In the video, he discusses the implementation of artificial intelligence in the detection of glaucoma in screening with photographs. Using this technology may bring down the undiagnosed rate of glaucoma, a disease with high rates of undiagnosed cases.
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There have been numerous studies showing that nearly half of glaucoma is undiagnosed in the United States—and it's even worse in developing countries. An interesting area of research that we're just beginning is the implementation of artificial intelligence in the detection of glaucoma in screening with photographs. There's a company in Australia that's already implemented this approach in optometric clinics, and we are adapting that software to our own patient populations.
What's unique about this approach is you can take a photo of a patient, it will automatically, immediately, analyze that photo on the computer. There is no transferring the photo to the web, which helps prevent HIPAA issues. It directly analyzes the photo and determines the likelihood of glaucoma being present. At the same time, it can also pick up other diseases like diabetic retinopathy or macular degeneration. We're very optimistic that this will be an important tool in identifying glaucoma in the region. If we can implement this successfully, we could greatly bring down the undiagnosed rate of glaucoma, and at the same time, start treatment earlier so that patients can receive the benefits of treatment at an earlier stage of the disease.
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