activity
20172022
most citedPredicting Risk of Developing Diabetic Retinopathy using Deep Learning

251 citations · 444 across the 6 of their papers we have counts for

collaborators

6 papers

eess.IV2022★ 2 cited

Discovering novel systemic biomarkers in photos of the external eye

Boris Babenko, Ilana Traynis, Christina Chen +16

External eye photos were recently shown to reveal signs of diabetic retinal disease and elevated HbA1c. In this paper, we evaluate if external eye photos contain information about…

cs.CV2022★ 32 cited

Robust and Efficient Medical Imaging with Self-Supervision

Shekoofeh Azizi, Laura Culp, Jan Freyberg +31

Recent progress in Medical Artificial Intelligence (AI) has delivered systems that can reach clinical expert level performance. However, such systems tend to demonstrate sub-optima…

eess.IV2020★ 100 cited

Detecting hidden signs of diabetes in external eye photographs

Boris Babenko, Akinori Mitani, Ilana Traynis +10

Diabetes-related retinal conditions can be detected by examining the posterior of the eye. By contrast, examining the anterior of the eye can reveal conditions affecting the front…

eess.IV2020★ 251 cited

Predicting Risk of Developing Diabetic Retinopathy using Deep Learning

Ashish Bora, Siva Balasubramanian, Boris Babenko +13

Diabetic retinopathy (DR) screening is instrumental in preventing blindness, but faces a scaling challenge as the number of diabetic patients rises. Risk stratification for the dev…

cs.CV2019★ 10 cited

Predicting Progression of Age-related Macular Degeneration from Fundus Images using Deep Learning

Boris Babenko, Siva Balasubramanian, Katy E. Blumer +5

Background: Patients with neovascular age-related macular degeneration (AMD) can avoid vision loss via certain therapy. However, methods to predict the progression to neovascular a…

stat.ML2017★ 49 cited

Poverty Mapping Using Convolutional Neural Networks Trained on High and Medium Resolution Satellite Images, With an Application in Mexico

Boris Babenko, Jonathan Hersh, David Newhouse +2

Mapping the spatial distribution of poverty in developing countries remains an important and costly challenge. These "poverty maps" are key inputs for poverty targeting, public goo…