A Model for Predicting 2-Year Risk of Incident Late Age-related Macular Degeneration
Full Description
PROJECT SUMMARY
Age-related macular degeneration (AMD), in the dry or wet form, is the leading cause of vision loss in
developed countries. The Age-Related Eye Disease Study (AREDS) showed that specific vitamin and mineral
supplementation reduces the risk of progression from intermediate stages to late AMD and maintains visual
acuity in approximately 25% of patients. While treatment of wet AMD with Intraocular injections can be
effective in maintaining vision, such treatments are costly and may be associated with significant
cardiovascular risks or even progression of dry AMD. Hence, it is critical to identify patients at the earlier
stages. With the NIH SBIR Phase II award, iHS has filled this market gap by developing iPredict-AMDTM, an
artificial intelligence (AI) based software for screening/early diagnosis and prediction of Late AMD,
which needs to be prospectively validated for FDA approval and commercialization. To accomplish this, the
prospective clinical trials for iPredict-AMD is required along with other studies such as human factor study
and precision study, which will be accomplished through this proposal.
Grant Number: 5R44EY031202-05
NIH Institute/Center: NIH
Principal Investigator: Alauddin Bhuiyan
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