FOR IMMEDIATE RELEASE
Media Contact:
Katrina Norfleet
+1.240.221.2924
knorfleet@arvo.org
Posted: 5/7/2017
Artificial intelligence predicts severe AMD development

 

After gathering optical coherence tomography (OCT) images of 38 patients’ retinas with early/intermediate AMD — every three months for a minimum of 15 months — researchers used the algorithm to accurately predict the occurrence of drusen regression within the next 12 months. While the presence of lipid/protein deposits called drusen is the hallmark of early/intermediate age-related macular degeneration (AMD), their sudden regression is strongly associated with the onset of late AMD.

Currently, there are no treatments for early/intermediate AMD. Anti-VEGF treatments for late AMD can prevent disease progression, but only after some vision loss has occurred. By pinpointing the moment of transition from early/intermediate to late AMD, the researchers state that machine learning will substantially contribute to the development of new therapeutics that target slowing AMD progression.

Abstract title: Personalized prognosis in early/intermediate age-related macular degeneration based on drusen regression
Presentation start/end time: Sunday, May 7, 2017, 8:30 – 10:15am
Location: Exhibit/Poster Hall
Abstract number: 15 - A0003

 

 

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The Association for Research in Vision and Ophthalmology (ARVO) is the largest eye and vision research organization in the world. Members include nearly 12,000 eye and vision researchers from over 75 countries. ARVO advances research worldwide into understanding the visual system and preventing, treating and curing its disorders.

All abstracts accepted for presentation at the ARVO Annual Meeting represent previously unpublished data and conclusions. This research may be proprietary or may have been submitted for journal publication. Embargo policy: Journalists must seek approval from the presenter(s) before reporting data from paper or poster presentations. Press releases or stories on information presented at the ARVO Annual Meeting may not be released or published until the conclusion of the presentation.

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