| Using a deep learning algorithm and integrated gradients explanation to assist grading for diabetic retinopathy R Sayres, A Taly, E Rahimy, K Blumer, D Coz, N Hammel, J Krause, ... Ophthalmology 126 (4), 552-564, 2019 | 432 | 2019 |
| Rates of retinal nerve fiber layer thinning in glaucoma suspect eyes A Miki, FA Medeiros, RN Weinreb, S Jain, F He, L Sharpsten, ... Ophthalmology 121 (7), 1350-1358, 2014 | 229 | 2014 |
| Predicting the risk of developing diabetic retinopathy using deep learning A Bora, S Balasubramanian, B Babenko, S Virmani, S Venugopalan, ... The Lancet Digital Health 3 (1), e10-e19, 2021 | 222 | 2021 |
| Detection of anaemia from retinal fundus images via deep learning A Mitani, A Huang, S Venugopalan, GS Corrado, L Peng, DR Webster, ... Nature biomedical engineering 4 (1), 18-27, 2020 | 218 | 2020 |
| Deep learning and glaucoma specialists: the relative importance of optic disc features to predict glaucoma referral in fundus photographs S Phene, RC Dunn, N Hammel, Y Liu, J Krause, N Kitade, ... Ophthalmology 126 (12), 1627-1639, 2019 | 192 | 2019 |
| Comparing the rates of retinal nerve fiber layer and ganglion cell–inner plexiform layer loss in healthy eyes and in glaucoma eyes N Hammel, A Belghith, RN Weinreb, FA Medeiros, N Mendoza, ... American journal of ophthalmology 178, 38-50, 2017 | 132 | 2017 |
| Detection of signs of disease in external photographs of the eyes via deep learning B Babenko, A Mitani, I Traynis, N Kitade, P Singh, AY Maa, J Cuadros, ... Nature biomedical engineering 6 (12), 1370-1383, 2022 | 66 | 2022 |
| Large-scale machine-learning-based phenotyping significantly improves genomic discovery for optic nerve head morphology B Alipanahi, F Hormozdiari, B Behsaz, J Cosentino, ZR McCaw, ... The American Journal of Human Genetics 108 (7), 1217-1230, 2021 | 61 | 2021 |
| The African Descent and Glaucoma Evaluation Study (ADAGES): predictors of visual field damage in glaucoma suspects N Khachatryan, FA Medeiros, L Sharpsten, C Bowd, PA Sample, ... American journal of ophthalmology 159 (4), 777-787. e1, 2015 | 60 | 2015 |
| Does the location of Bruch's membrane opening change over time? Longitudinal analysis using San Diego Automated Layer Segmentation Algorithm (SALSA) A Belghith, C Bowd, FA Medeiros, N Hammel, Z Yang, RN Weinreb, ... Investigative ophthalmology & visual science 57 (2), 675-682, 2016 | 55 | 2016 |
| Diagnostic accuracy of the spectralis and cirrus reference databases in differentiating between healthy and early glaucoma eyes AL Silverman, N Hammel, N Khachatryan, L Sharpsten, FA Medeiros, ... Ophthalmology 123 (2), 408-414, 2016 | 50 | 2016 |
| Lessons learned from translating AI from development to deployment in healthcare K Widner, S Virmani, J Krause, J Nayar, R Tiwari, ER Pedersen, D Jeji, ... Nature Medicine 29 (6), 1304-1306, 2023 | 46 | 2023 |
| Deep learning to detect OCT-derived diabetic macular edema from color retinal photographs: a multicenter validation study X Liu, TK Ali, P Singh, A Shah, SM McKinney, P Ruamviboonsuk, ... Ophthalmology Retina 6 (5), 398-410, 2022 | 36 | 2022 |
| Association of severity of primary open-angle glaucoma with serum vitamin D levels in patients of African descent R Ayyagari, C Yii-der I, LM Zangwill, M Holman, K Dirkes, Y Hai, ... Molecular Vision 25, 438, 2019 | 30 | 2019 |
| Intravenous immunoglobulin in recurrent-relapsing inflammatory optic neuropathy H Stiebel-Kalish, N Hammel, J Van Everdingen, R Huna-Baron, AG Lee Canadian Journal of Ophthalmology 45 (1), 71-75, 2010 | 30 | 2010 |
| Changes in anterior segment parameters after insertion of Ex-PRESS miniature glaucoma implant N Hammel, M Lusky, I Kaiserman, A Robinson, I Bahar Journal of Glaucoma 22 (7), 565-568, 2013 | 29 | 2013 |
| Quantitative trait locus analysis of SIX1-SIX6 with retinal nerve fiber layer thickness in individuals of European descent JZ Kuo, LM Zangwill, FA Medeiros, JM Liebmann, CA Girkin, N Hammel, ... American journal of ophthalmology 160 (1), 123-130. e1, 2015 | 28 | 2015 |
| Rate and pattern of rim area loss in healthy and progressing glaucoma eyes N Hammel, A Belghith, C Bowd, FA Medeiros, L Sharpsten, N Mendoza, ... Ophthalmology 123 (4), 760-770, 2016 | 27 | 2016 |
| Using generative AI to investigate medical imagery models and datasets O Lang, D Yaya-Stupp, I Traynis, H Cole-Lewis, CR Bennett, CR Lyles, ... EBioMedicine 102, 2024 | 24 | 2024 |
| A deep learning model for novel systemic biomarkers in photographs of the external eye: a retrospective study B Babenko, I Traynis, C Chen, P Singh, A Uddin, J Cuadros, LP Daskivich, ... The Lancet Digital Health 5 (5), e257-e264, 2023 | 24 | 2023 |
Dale R WebsterResearch Director, GoogleVerified email at google.com
