| Development and validation of a deep learning algorithm for detection of diabetic retinopathy in retinal fundus photographs V Gulshan, L Peng, M Coram, MC Stumpe, D Wu, A Narayanaswamy, ... jama 316 (22), 2402-2410, 2016 | 7453 | 2016 |
| Artificial intelligence and deep learning in ophthalmology DSW Ting, LR Pasquale, L Peng, JP Campbell, AY Lee, R Raman, ... British Journal of Ophthalmology 103 (2), 167-175, 2019 | 1193 | 2019 |
| Underspecification presents challenges for credibility in modern machine learning A D'Amour, K Heller, D Moldovan, B Adlam, B Alipanahi, A Beutel, ... Journal of Machine Learning Research 23 (226), 1-61, 2022 | 788 | 2022 |
| Prevalence of diabetic retinopathy in India: Sankara Nethralaya diabetic retinopathy epidemiology and molecular genetics study report 2 R Raman, PK Rani, SR Rachepalle, P Gnanamoorthy, S Uthra, ... Ophthalmology 116 (2), 311-318, 2009 | 470 | 2009 |
| Knowledge of diabetes and diabetic retinopathy among rural populations in India, and the influence of knowledge of diabetic retinopathy on attitude and practice PK Rani, R Raman, S Subramani, G Perumal, G Kumaramanickavel, ... Rural and remote health 8 (3), 1-9, 2008 | 278 | 2008 |
| Performance of a deep-learning algorithm vs manual grading for detecting diabetic retinopathy in India V Gulshan, RP Rajan, K Widner, D Wu, P Wubbels, T Rhodes, ... JAMA ophthalmology 137 (9), 987-993, 2019 | 248 | 2019 |
| Deep learning versus human graders for classifying diabetic retinopathy severity in a nationwide screening program P Ruamviboonsuk, J Krause, P Chotcomwongse, R Sayres, R Raman, ... NPJ digital medicine 2 (1), 25, 2019 | 228* | 2019 |
| Is neuronal dysfunction an early sign of diabetic retinopathy? Microperimetry and spectral domain optical coherence tomography (SD-OCT) study in individuals with diabetes, but … A Verma, PK Rani, R Raman, SS Pal, G Laxmi, M Gupta, C Sahu, ... Eye 23 (9), 1824-1830, 2009 | 206 | 2009 |
| Prevalence and risk factors for diabetic retinopathy in rural India. Sankara Nethralaya Diabetic Retinopathy Epidemiology and Molecular Genetic Study III (SN-DREAMS III … R Raman, S Ganesan, SS Pal, V Kulothungan, T Sharma BMJ Open Diabetes Research and Care 2 (1), e000005, 2014 | 203 | 2014 |
| Deep learning architecture based on segmented fundus image features for classification of diabetic retinopathy S Das, K Kharbanda, M Suchetha, R Raman, E Dhas Biomedical Signal Processing and Control 68, 102600, 2021 | 178 | 2021 |
| Risk factors for diabetic retinopathy in self-reported rural population with diabetes PK Rani, R Raman, A Chandrakantan, SS Pal, GM Perumal, T Sharma Journal of postgraduate medicine 55 (2), 92-96, 2009 | 165 | 2009 |
| Fundus photograph-based deep learning algorithms in detecting diabetic retinopathy R Raman, S Srinivasan, S Virmani, S Sivaprasad, C Rao, R Rajalakshmi Eye 33 (1), 97-109, 2019 | 155 | 2019 |
| Changes in the corneal endothelial cell density and morphology in patients with type 2 diabetes mellitus: a population-based study, Sankara Nethralaya Diabetic Retinopathy and … RR Sudhir, R Raman, T Sharma Cornea 31 (10), 1119-1122, 2012 | 153 | 2012 |
| Prevalence and risk factors for diabetic microvascular complications in newly diagnosed type II diabetes mellitus. Sankara Nethralaya Diabetic Retinopathy Epidemiology and … R Raman, A Gupta, S Krishna, V Kulothungan, T Sharma Journal of Diabetes and its Complications 26 (2), 123-128, 2012 | 153 | 2012 |
| Does neuronal damage precede vascular damage in subjects with type 2 diabetes mellitus and having no clinical diabetic retinopathy? A Verma, R Raman, K Vaitheeswaran, SS Pal, G Laxmi, M Gupta, ... Ophthalmic research 47 (4), 202-207, 2012 | 134 | 2012 |
| Real-time diabetic retinopathy screening by deep learning in a multisite national screening programme: a prospective interventional cohort study P Ruamviboonsuk, R Tiwari, R Sayres, V Nganthavee, K Hemarat, ... The Lancet Digital Health 4 (4), e235-e244, 2022 | 129 | 2022 |
| Sankara Nethralaya—Diabetic retinopathy epidemiology and molecular genetic study (SN—DREAMS 1): Study design and research methodology S Agarwal, R Raman, PG Paul, PK Rani, S Uthra, R Gayathree, ... Ophthalmic epidemiology 12 (2), 143-153, 2005 | 125 | 2005 |
| The prevalence and risk factors for cataract in rural and urban India S Singh, S Pardhan, V Kulothungan, G Swaminathan, JS Ravichandran, ... Indian journal of ophthalmology 67 (4), 477-483, 2019 | 121 | 2019 |
| Association of obesity with diabetic retinopathy: Sankara Nethralaya Diabetic Retinopathy Epidemiology and Molecular Genetics Study (SN-DREAMS Report no. 8) R Raman, PK Rani, P Gnanamoorthy, RR Sudhir, G Kumaramanikavel, ... Acta diabetologica 47, 209-215, 2010 | 115 | 2010 |
| Diabetic retinopathy: An epidemic at home and around the world R Raman, L Gella, S Srinivasan, T Sharma Indian journal of ophthalmology 64 (1), 69-75, 2016 | 111 | 2016 |