Institution · Eyenuk (United States)
Most cited papers from Eyenuk (United States)
What are the most cited papers from Eyenuk (United States)?
The most cited paper from Eyenuk (United States) is "Pivotal Evaluation of an Artificial Intelligence System for Autonomous Detection of Referrable and Vision-Threatening Diabetic Retinopathy" (Eli Ipp et al., 2021), with 250 citations. Next come "The Value of Automated Diabetic Retinopathy Screening with the EyeArt System: A Study of More Than 100,000 Consecutive Encounters from People with Diabetes" (211) and "Artificial Intelligence Detection of Diabetic Retinopathy" (157).
Showing 32 of 32 papers. Every paper is listed.
| # | Paper | ||
|---|---|---|---|
| 1 | Pivotal Evaluation of an Artificial Intelligence System for Autonomous Detection of Referrable and Vision-Threatening Diabetic Retinopathy Eli Ipp et al. · JAMA Network Open | 15 Nov 2021 | 250 |
| 2 | The Value of Automated Diabetic Retinopathy Screening with the EyeArt System: A Study of More Than 100,000 Consecutive Encounters from People with Diabetes Malavika Bhaskaranand, Chaithanya A. Ramachandra, Sandeep Bhat et al. · Diabetes Technology & Therapeutics | 23 Jul 2019 | 211 |
| 3 | Artificial Intelligence Detection of Diabetic Retinopathy Jennifer I. Lim et al. · Ophthalmology Science | 30 Sep 2022 | 157 |
| 4 | Automated Diabetic Retinopathy Screening and Monitoring Using Retinal Fundus Image Analysis Malavika Bhaskaranand, Chaithanya A. Ramachandra, Sandeep Bhat et al. · Journal of Diabetes Science and Technology | 16 Feb 2016 | 124 |
| 5 | Diabetic Retinopathy Screening with Automated Retinal Image Analysis in a Primary Care Setting Improves Adherence to Ophthalmic Care James Liu, Ella Gibson, Shawn Ramchal et al. · Ophthalmology Retina | 17 Jun 2020 | 89 |
| 6 | EyeArt: Automated, High-throughput, Image Analysis for Diabetic Retinopathy Screening Kaushal V. Solanki, Chaithanya A. Ramachandra, Sandeep Bhat et al. · Investigative Ophthalmology & Visual Science | 11 Jun 2015 | 34 |
| 7 | Automated detection of diabetic retinopathy lesions on ultrawidefield pseudocolour images Kang Wang, Chaitra Jayadev, Muneeswar Gupta Nittala et al. · Acta Ophthalmologica | 19 Sep 2017 | 29 |
| 8 | Comparison of diabetic retinopathy severity grading on ETDRS 7-field versus ultrawide-field assessment Yamini Attiku, Muneeswar Gupta Nittala, Swetha Bindu Velaga et al. · Eye | 10 May 2023 | 27 |
| 9 | EyeArt + EyePACS: Automated Retinal Image Analysis For Diabetic Retinopathy Screening in a Telemedicine System Malavika Bhaskaranand, Jorge A. Cuadros, Chaithanya A. Ramachandra et al. | 15 Sep 2015 | 19 |
| 10 | A pilot cost-analysis study comparing AI-based EyeArt® and ophthalmologist assessment of diabetic retinopathy in minority women in Oslo, Norway Mia Karabeg, Goran Petrovski, Silvia N. W. Hertzberg et al. · International Journal of Retina and Vitreous | 23 May 2024 | 18 |
| 11 | Diabetic Retinopathy Screening in Patients with Diabetes Using a Handheld Fundus Camera: The Experience from the South-Eastern Region in Hungary Dóra Júlia Eszes, Dóra Júlia Szabó, Greg Russell et al. · Journal of Diabetes Research | 8 Feb 2021 | 13 |
| 12 | Diabetic Retinopathy Screening Among Federally Qualified Health Center Patients Using Point-of-Care AI Edgar A. Diaz, Marva Seifert, Vida Gruning et al. · JAMA Network Open | 21 Oct 2025 | 9 |
| 13 | Fully-automated Diabetic Retinopathy Screening Using Cellphone-based Cameras Sandeep Bhat, Malavika Bhaskaranand, Chaithanya A. Ramachandra et al. · Investigative Ophthalmology & Visual Science | 11 Jun 2015 | 6 |
| 14 | Classical-Contextual Interactions in V1 May Rely on Dendritic Computations Lei Jin, Bardia F. Behabadi, Monica P. Jadi et al. · Neuroscience | 7 Mar 2022 | 4 |
| 15 | Comparison of Validity and Reliability of Manual Consensus Grading vs. Automated AI Grading for Diabetic Retinopathy Screening in Oslo, Norway: A Cross-Sectional Pilot Study Mia Karabeg, Goran Petrovski, Katrine Holen et al. · Journal of Clinical Medicine | 7 Jul 2025 | 3 |
| 16 | Digital Image Analysis of the Angle and Optic Nerve: A Simple, Fast, and Low-Cost Method for Glaucoma Assessment Greg Russell, Silvia N. W. Hertzberg, Natalia S. Anisimova et al. · Journal of Ophthalmology | 28 Oct 2020 | 3 |
| 17 | Comparison of automated and expert human grading of diabetic retinopathy using smartphone-based retinal photography Tyson N. Kim, Michael T. Aaberg, Patrick Li et al. · Eye | 27 Apr 2020 | 3 |
| 18 | Advanced retinal image analysis for AMD screening applications Chaithanya A. Ramachandra, Sandeep Bhat, Malavika Bhaskaranand et al. · Investigative Ophthalmology & Visual Science | 11 Jun 2015 | 3 |
| 19 | Predicting progression to proliferative diabetic retinopathy using automated versus manual quantification of retinal haemorrhages Aditya Verma, Muneeswar G. Nittala, Roxan Mansoori Dara et al. · Eye | 16 Jan 2026 | 2 |
| 20 | IDF21-0386 DFU Track: Building a novel, Artificial Intelligence-based method to monitor wound healing R. Ravenscroft, A. J. M. Boulton, L. Vileikyte et al. · Diabetes Research and Clinical Practice | Apr 2022 | 2 |
| 21 | Object boundary detection in natural images may depend on ‘incitatory’ cell-cell interactions Gabriel C. Mel, Chaithanya A. Ramachandra, Bartlett W. Mel · bioRxiv (Cold Spring Harbor Laboratory) | 7 Oct 2018 | 2 |
| 22 | Automated image analysis for Diabetic Retinopathy Screening with iPhone-based fundus camera Sandeep Bhat, Malavika Bhaskaranand, Chaithanya A. Ramachandra et al. · Investigative Ophthalmology & Visual Science | 26 Sep 2016 | 2 |
| 23 | EyeArt: Advanced Image Analysis Tools for Diabetic Retinopathy Screening and Telemedicine Applications Kaushal V. Solanki, Sandeep Bhat, Chaithanya A. Ramachandra et al. · Investigative Ophthalmology & Visual Science | 30 Apr 2014 | 1 |
| 24 | Diabetic Retinopathy Screening in a Primary Care Setting Using Non-Mydriatic Photography and Automated Retinal Image Analysis Improves Compliance with Follow-Up Ophthalmic Care James Liu, Vikram A. Shankar, Shawn Ramchal et al. · Investigative Ophthalmology & Visual Science | 22 Jul 2019 | 0 |
| 25 | Deep neural network and human evaluation of referral-warranted diabetic retinopathy using smartphone-based retinal photographs Michael T. Aaberg, Tyson N. Kim, Patrick Li et al. · Investigative Ophthalmology & Visual Science | 22 Jul 2019 | 0 |
| 26 | Clinical Validation of Diabetic Retinopathy Lesion Segmentation in Ultra-Widefield images Sandeep Bhat, Christian Siagian, Chaithanya A. Ramachandra et al. · Investigative Ophthalmology & Visual Science | 13 Jul 2018 | 0 |
| 27 | Validation of EyeArt Automated Diabetic Retinopathy Screening System on large cohort of mydriatic and non mydriatic telescreening data from EyePACS Kaushal V. Solanki, Malavika Bhaskaranand, Chaithanya A. Ramachandra et al. · Investigative Ophthalmology & Visual Science | 23 Jun 2017 | 0 |
| 28 | Cost Savings Enabled by Automated Diabetic Retinopathy Screening in a UK-like screening program Malavika Bhaskaranand, Chaithanya A. Ramachandra, Sandeep Bhat et al. · Investigative Ophthalmology & Visual Science | 26 Sep 2016 | 0 |
| 29 | Real world, Large-scale Study of Safety and Effectiveness of a Fully-automated Diabetic Retinopathy Screening System Kaushal V. Solanki, Chaithanya A. Ramachandra, Sandeep Bhat et al. · Investigative Ophthalmology & Visual Science | 26 Sep 2016 | 0 |
| 30 | Advanced Image Enhancement and Analysis Tools for Image Quality Assessment Sandeep Bhat, Chaithanya A. Ramachandra, Muneeswar Gupta Nittala et al. · Investigative Ophthalmology & Visual Science | 30 Apr 2014 | 0 |
| 31 | Automated vasculature segmentation in retinal images using multi-scale image analysis Malavika Bhaskaranand, Chaithanya A. Ramachandra, Sandeep Bhat et al. · Investigative Ophthalmology & Visual Science | 11 Jun 2015 | 0 |
| 32 | EyeMark: Automated Image-based Biomarker Computation Tools for Monitoring Diabetic Retinopathy Chaithanya A. Ramachandra, Sandeep Bhat, Muneeswar Gupta Nittala et al. · Investigative Ophthalmology & Visual Science | 30 Apr 2014 | 0 |
Citations are OpenAlex's own counts, from its 2026-09-23 snapshot, so the ranking can differ from Google Scholar or Web of Science. A paper is listed for an institution when any of its authors gave it as an affiliation; retracted papers and papers whose citation count cannot be traced to citing works are left out, and a preprint and the article it became are shown once. Release dates are OpenAlex's: where a source gave only a month or a year, that is what is shown. How the lists are chosen.