Articles with public access mandates - Chaithanya RamachandraLearn more
Available somewhere: 13
The value of automated diabetic retinopathy screening with the EyeArt system: a study of more than 100,000 consecutive encounters from people with diabetes
M Bhaskaranand, C Ramachandra, S Bhat, J Cuadros, MG Nittala, ...
Diabetes technology & therapeutics 21 (11), 635-643, 2019
Mandates: US National Institutes of Health
Pivotal evaluation of an artificial intelligence system for autonomous detection of referrable and vision-threatening diabetic retinopathy
E Ipp, D Liljenquist, B Bode, VN Shah, S Silverstein, CD Regillo, JI Lim, ...
JAMA network open 4 (11), e2134254-e2134254, 2021
Mandates: US National Institutes of Health
Automated diabetic retinopathy screening and monitoring using retinal fundus image analysis
M Bhaskaranand, C Ramachandra, S Bhat, J Cuadros, MG Nittala, ...
Journal of diabetes science and technology 10 (2), 254-261, 2016
Mandates: US National Institutes of Health
Artificial intelligence detection of diabetic retinopathy: subgroup comparison of the EyeArt system with ophthalmologists’ dilated examinations
JI Lim, CD Regillo, SVR Sadda, E Ipp, M Bhaskaranand, C Ramachandra, ...
Ophthalmology science 3 (1), 100228, 2023
Mandates: US National Institutes of Health
Contour enhancement benefits older adults with simulated central field loss
MY Kwon, C Ramachandra, PN Satgunam, BW Mel, E Peli, BS Tjan
Optometry and vision science 89 (9), 1374-1384, 2012
Mandates: US National Institutes of Health
Effects of contour enhancement on low-vision preference and visual search
PN Satgunam, RL Woods, G Luo, PM Bronstad, Z Reynolds, ...
Optometry and vision science 89 (9), E1364-E1373, 2012
Mandates: US National Institutes of Health
Automated detection of diabetic retinopathy lesions on ultrawidefield pseudocolour images
K Wang, C Jayadev, MG Nittala, SB Velaga, CA Ramachandra, ...
Acta Ophthalmologica 96 (2), e168-e173, 2018
Mandates: US National Institutes of Health
Comparison of automated and expert human grading of diabetic retinopathy using smartphone-based retinal photography
TN Kim, MT Aaberg, P Li, JR Davila, M Bhaskaranand, S Bhat, ...
Eye 35 (1), 334-342, 2021
Mandates: US National Institutes of Health, Chan Zuckerberg Initiative
Computing local edge probability in natural scenes from a population of oriented simple cells
CA Ramachandra, BW Mel
Journal of Vision 13 (14), 19-19, 2013
Mandates: US National Institutes of Health
Classical-contextual interactions in V1 may rely on dendritic computations
L Jin, BF Behabadi, MP Jadi, CA Ramachandra, BW Mel
Neuroscience 489, 234-250, 2022
Mandates: US National Institutes of Health
Detecting object boundaries in natural images requires ‘incitatory’cell-cell interactions
GC Mel, CA Ramachandra, BW Mel
Cortex 22 (19), 8633-46, 2018
Mandates: US National Institutes of Health
Object Boundary Detection in Natural Images May Depend on “Incitatory” Cell–Cell Interactions
GC Mel, CA Ramachandra, BW Mel
Journal of Neuroscience 42 (48), 8960-8979, 2022
Mandates: US National Institutes of Health
Real world, Large-scale Study of Safety and Effectiveness of a Fully-automated Diabetic Retinopathy Screening System
K Solanki, C Ramachandra, S Bhat, M Bhaskaranand, M gupta Nittala, ...
Investigative Ophthalmology & Visual Science 57 (12), 1720-1720, 2016
Mandates: US National Institutes of Health
Publication and funding information is determined automatically by a computer program