Articles with public access mandates - Siegfried WagnerLearn more
Not available anywhere: 1
CF-Loss: Clinically-relevant feature optimised loss function for retinal multi-class vessel segmentation and vascular feature measurement
Y Zhou, MC Xu, Y Hu, SB Blumberg, A Zhao, SK Wagner, PA Keane, ...
Medical Image Analysis 93, 103098, 2024
Mandates: UK Engineering and Physical Sciences Research Council, National Institute …
Available somewhere: 68
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
Mandates: UK Medical Research Council, National Institute for Health Research, UK …
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
Mandates: UK Medical Research Council, National Institute for Health Research, UK
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
Mandates: UK Medical Research Council, National Institute for Health Research, UK …
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
Mandates: UK Engineering and Physical Sciences Research Council, UK Medical Research …
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
Mandates: US Department of Veterans Affairs, UK Medical Research Council, National …
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
Mandates: UK Medical Research Council
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
Mandates: National Institute for Health Research, UK
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
Mandates: US Department of Veterans Affairs, UK Medical Research Council, National …
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
Mandates: UK Medical Research Council, National Institute for Health Research, UK, UK …
Optical coherence tomography in the 2020s—outside the eye clinic
R Chopra, SK Wagner, PA Keane
Eye 35 (1), 236-243, 2021
Mandates: UK Medical Research Council, UK Research & Innovation
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
Mandates: UK Medical Research Council, National Institute for Health Research, UK …
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
Mandates: UK Medical Research Council
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
Mandates: US National Institutes of Health, UK Engineering and Physical Sciences …
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
Mandates: Alzheimers's UK, UK Engineering and Physical Sciences Research Council, UK …
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
Mandates: US Department of Defense, US National Institutes of Health, Canadian …
Transcorneal electrical stimulation for the treatment of retinitis pigmentosa: results from the TESOLAUK trial
SK Wagner, JK Jolly, M Pefkianaki, F Gekeler, AR Webster, SM Downes, ...
BMJ Open Ophthalmology 2 (1), e000096, 2017
Mandates: National Institute for Health Research, UK, Wellcome Trust
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
Mandates: UK Medical Research Council, National Institute for Health Research, UK …
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
Mandates: UK Medical Research Council, National Institute for Health Research, UK, UK …
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
Mandates: US National Institutes of Health, UK Medical Research Council, National …
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