A comparison of deep learning performance against health-care professionals in detecting diseases from medical imaging: a systematic review and meta-analysis X Liu, L Faes, AU Kale, SK Wagner, DJ Fu, A Bruynseels, T Mahendiran, ... The lancet digital health 1 (6), e271-e297, 2019 | 1589 | 2019 |
Automated deep learning design for medical image classification by health-care professionals with no coding experience: a feasibility study L Faes, SK Wagner, DJ Fu, X Liu, E Korot, JR Ledsam, T Back, R Chopra, ... The Lancet Digital Health 1 (5), e232-e242, 2019 | 272 | 2019 |
A global review of publicly available datasets for ophthalmological imaging: barriers to access, usability, and generalisability SM Khan, X Liu, S Nath, E Korot, L Faes, SK Wagner, PA Keane, ... The Lancet Digital Health 3 (1), e51-e66, 2021 | 260 | 2021 |
A foundation model for generalizable disease detection from retinal images Y Zhou, MA Chia, SK Wagner, MS Ayhan, DJ Williamson, RR Struyven, ... Nature 622 (7981), 156-163, 2023 | 235 | 2023 |
Insights into systemic disease through retinal imaging-based oculomics SK Wagner, DJ Fu, L Faes, X Liu, J Huemer, H Khalid, D Ferraz, E Korot, ... Translational vision science & technology 9 (2), 6-6, 2020 | 183 | 2020 |
Bidirectional Ca2+ signaling occurs between the endoplasmic reticulum and acidic organelles AJ Morgan, LC Davis, SKTY Wagner, AM Lewis, J Parrington, ... Journal of Cell Biology 200 (6), 789-805, 2013 | 176 | 2013 |
A clinician's guide to artificial intelligence: how to critically appraise machine learning studies L Faes, X Liu, SK Wagner, DJ Fu, K Balaskas, DA Sim, LM Bachmann, ... Translational vision science & technology 9 (2), 7-7, 2020 | 148 | 2020 |
Code-free deep learning for multi-modality medical image classification E Korot, Z Guan, D Ferraz, SK Wagner, G Zhang, X Liu, L Faes, ... Nature Machine Intelligence 3 (4), 288-298, 2021 | 142 | 2021 |
Predicting sex from retinal fundus photographs using automated deep learning E Korot, N Pontikos, X Liu, SK Wagner, L Faes, J Huemer, K Balaskas, ... Scientific reports 11 (1), 10286, 2021 | 114 | 2021 |
Quantitative analysis of OCT for neovascular age-related macular degeneration using deep learning G Moraes, DJ Fu, M Wilson, H Khalid, SK Wagner, E Korot, D Ferraz, ... Ophthalmology 128 (5), 693-705, 2021 | 98 | 2021 |
Optical coherence tomography in the 2020s—outside the eye clinic R Chopra, SK Wagner, PA Keane Eye 35 (1), 236-243, 2021 | 68 | 2021 |
Clinically relevant deep learning for detection and quantification of geographic atrophy from optical coherence tomography: a model development and external validation study G Zhang, DJ Fu, B Liefers, L Faes, S Glinton, S Wagner, R Struyven, ... The Lancet Digital Health 3 (10), e665-e675, 2021 | 63 | 2021 |
The evolution of diabetic retinopathy screening programmes: a chronology of retinal photography from 35 mm slides to artificial intelligence J Huemer, SK Wagner, DA Sim Clinical Ophthalmology, 2021-2035, 2020 | 49 | 2020 |
AutoMorph: automated retinal vascular morphology quantification via a deep learning pipeline Y Zhou, SK Wagner, MA Chia, A Zhao, M Xu, R Struyven, DC Alexander, ... Translational vision science & technology 11 (7), 12-12, 2022 | 44 | 2022 |
AlzEye: longitudinal record-level linkage of ophthalmic imaging and hospital admissions of 353 157 patients in London, UK SK Wagner, F Hughes, M Cortina-Borja, N Pontikos, R Struyven, X Liu, ... BMJ open 12 (3), e058552, 2022 | 40 | 2022 |
Artificial intelligence extension of the OSCAR‐IB criteria A Petzold, P Albrecht, L Balcer, E Bekkers, AU Brandt, PA Calabresi, ... Annals of clinical and translational neurology 8 (7), 1528-1542, 2021 | 38 | 2021 |
Retinal optical coherence tomography features associated with incident and prevalent Parkinson disease SK Wagner, D Romero-Bascones, M Cortina-Borja, DJ Williamson, ... Neurology 101 (16), e1581-e1593, 2023 | 37 | 2023 |
Enablers and barriers to deployment of smartphone-based home vision monitoring in clinical practice settings E Korot, N Pontikos, FM Drawnel, A Jaber, DJ Fu, G Zhang, MA Miranda, ... JAMA ophthalmology 140 (2), 153-160, 2022 | 34 | 2022 |
Predicting incremental and future visual change in neovascular age-related macular degeneration using deep learning DJ Fu, L Faes, SK Wagner, G Moraes, R Chopra, PJ Patel, K Balaskas, ... Ophthalmology Retina 5 (11), 1074-1084, 2021 | 34 | 2021 |
Moorfields AMD database report 2: fellow eye involvement with neovascular age-related macular degeneration K Fasler, DJ Fu, G Moraes, S Wagner, E Gokhale, K Kortuem, R Chopra, ... British Journal of Ophthalmology 104 (5), 684-690, 2020 | 34 | 2020 |