This Project Grant award from the National Eye Institute (NEI) under the Vision Research program (CFDA 93.867) is supporting the development of equitable deep learning models for automated glaucoma screening. The $754,779 award, with a performance period from Sep 30, 2024 to Jul 31, 2029, aims to assess the performance equity of existing deep learning models, develop identity-conditioned generative models to improve data equality, and create fair identity normalization techniques to equalize...
This federal Project Grant award from the National Eye Institute (CFDA 93.867 - Vision Research) provides $628,531 to the University of Miami to validate and implement an artificial intelligence machine-to-machine (M2M) model for equitable glaucoma screening in underserved populations. The M2M model aims to provide objective, quantitative assessments of glaucomatous damage from low-cost fundus photography, overcoming limitations of existing imaging technologies. The project will refine the M2M...
The National Eye Institute (NEI) has awarded a $466,125 Federal Project Grant (CFDA 93.867 - Vision Research) to Weill Medical College of Cornell University to develop and validate a new artificial intelligence approach to improve the fairness of predictive models for primary open-angle glaucoma (POAG) risk estimation. The project aims to study algorithmic bias in POAG risk prediction and examine the impact of transferring bias from a biased model to a demographically balanced dataset. The...
This federal Project Grant award from the National Eye Institute (CFDA 93.867 Vision Research) provides $617,201 in funding to Emory University to conduct research aimed at improving the understanding and management of glaucoma, a leading cause of blindness. The key research objectives are to: 1) Map the 3D paths of optic nerve axons using optical coherence tomography (OCT) imaging; 2) Leverage AI to assess whether axonal deformations could serve as diagnostic and prognostic biomarkers for...
This federal Project Grant award from the National Eye Institute (CFDA 93.867 - Vision Research) aims to develop an "Attentive Knowledge Device for Visual Assistance" that leverages artificial intelligence (AI) and computer vision technologies to better assist persons with visual impairment. The $602,198 award, effective July 1, 2025 through June 30, 2027, will fund the University of Southern California to: 1) engage partners to select optimal machine vision algorithms for real-time...
This Project Grant award from the National Human Genome Research Institute (CFDA 93.172 - Human Genome Research) provides $499,530 to The Leland Stanford Junior University to assess how diversity and representation are conceptualized and implemented in 50 NIH-funded artificial intelligence for healthcare (AI-HC) research projects. The goal is to develop practical, evidence-informed guidance to support fairness in AI-HC dataset development. The project will involve reviewing policy documents,...
This federal Project Grant award of $715,098 from the National Eye Institute (NEI) under the Vision Research program (CFDA 93.867) aims to enhance glaucoma risk prediction through advanced genomics and machine learning. The key products and services to be delivered include: Improving polygenic risk score (PRS) performance for glaucoma by leveraging natural language processing techniques and electronic health record data from over 68,000 patients to extract refined glaucoma phenotypes. The...
This Project Grant award from the National Eye Institute (NEI), under the federal Vision Research program (CFDA 93.867), provides $247,387 to Stanford University to establish a comprehensive strategy for recruiting, training, and retaining clinician-scientists in ophthalmology research. The overarching objectives are to educate and develop the next generation of clinician-scientists focused on vision-related diseases and disorders, and to enhance research capabilities within ophthalmology...
This $433,841 federal Project Grant award from the National Eye Institute (NEI) under the Vision Research program (CFDA 93.867) supports the development of computational methods and deep learning models to analyze imaging data and identify biomarkers for age-related macular degeneration (AMD). The goal is to improve understanding of AMD disease progression and response to treatment. Specifically, the project will develop deep neural network models to analyze optical coherence tomography,...
This Project Grant award from the National Eye Institute (NEI), under the Vision Research program (CFDA 93.867), provides $450,002.00 to The Trustees of the University of Pennsylvania to develop robust and equitable clinical decision support systems for glaucoma detection and progression prediction. The project will run from September 1, 2024 to August 31, 2028. The University of Pennsylvania, a leading academic medical center, will leverage its expertise in biomedical research and healthcare...