Artigos com autorizações de acesso público - Livia Faes, MSc MDSaiba mais
1 artigo não disponível publicamente
Artificial intelligence in ophthalmology: Guidelines for physicians for the critical evaluation of studies
M Pfau, G Walther, L von der Emde, P Berens, L Faes, M Fleckenstein, ...
Der Ophthalmologe 117, 973-988, 2020
Autorizações: German Research Foundation
45 artigos disponíveis publicamente
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
Autorizações: UK Medical Research Council, National Institute for Health Research, UK …
Reporting guidelines for clinical trial reports for interventions involving artificial intelligence: the CONSORT-AI extension
X Liu, SC Rivera, D Moher, MJ Calvert, AK Denniston, H Ashrafian, ...
The Lancet Digital Health 2 (10), e537-e548, 2020
Autorizações: US National Institutes of Health, UK Engineering and Physical Sciences …
Guidelines for clinical trial protocols for interventions involving artificial intelligence: the SPIRIT-AI extension
SC Rivera, X Liu, AW Chan, AK Denniston, MJ Calvert, H Ashrafian, ...
The Lancet Digital Health 2 (10), e549-e560, 2020
Autorizações: US National Institutes of Health, UK Engineering and Physical Sciences …
Reporting guideline for the early stage clinical evaluation of decision support systems driven by artificial intelligence: DECIDE-AI
B Vasey, M Nagendran, B Campbell, DA Clifton, GS Collins, S Denaxas, ...
bmj 377, 2022
Autorizações: US National Science Foundation, US National Institutes of Health, American …
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
Autorizações: 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
Autorizações: UK Medical Research Council, National Institute for Health Research, UK …
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
Autorizações: 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
Autorizações: 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
Autorizações: 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
Autorizações: 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
Autorizações: UK Medical Research Council, National Institute for Health Research, UK, UK …
Reporting guidelines for clinical trials evaluating artificial intelligence interventions are needed
Nature Medicine 25 (10), 1467-1468, 2019
Autorizações: Wellcome Trust, Health Data Research, UK
Extension of the CONSORT and SPIRIT statements
X Liu, L Faes, MJ Calvert, AK Denniston
The Lancet 394 (10205), 1225, 2019
Autorizações: Wellcome Trust, Health Data Research, UK
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
Autorizações: UK Medical Research Council, National Institute for Health Research, UK …
Causes of low neonatal T-cell receptor excision circles: a systematic review
AA Mauracher, F Pagliarulo, L Faes, S Vavassori, T Güngör, ...
The Journal of Allergy and Clinical Immunology: In Practice 5 (5), 1457-1460 …, 2017
Autorizações: Swiss National Science Foundation
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
Autorizações: UK Medical Research Council, National Institute for Health Research, UK, UK …
Will AI replace ophthalmologists?
E Korot, SK Wagner, L Faes, X Liu, J Huemer, D Ferraz, PA Keane, ...
Translational vision science & technology 9 (2), 2-2, 2020
Autorizações: US Department of Veterans Affairs, UK Medical Research Council, National …
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
Autorizações: US National Institutes of Health, UK Medical Research Council, National …
One-and two-year visual outcomes from the Moorfields age-related macular degeneration database: a retrospective cohort study and an open science resource
K Fasler, G Moraes, S Wagner, KU Kortuem, R Chopra, L Faes, G Preston, ...
BMJ open 9 (6), e027441, 2019
Autorizações: US National Institutes of Health, National Institute for Health Research, UK
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