User profiles for "author:Siegfried Wagner"

Siegfried Wagner

University College London
Verified email at ucl.ac.uk
Cited by 3274

[HTML][HTML] A comparison of deep learning performance against health-care professionals in detecting diseases from medical imaging: a systematic review and meta …

X Liu, L Faes, AU Kale, SK Wagner, DJ Fu… - The lancet digital …, 2019 - thelancet.com
Background Deep learning offers considerable promise for medical diagnostics. We aimed
to evaluate the diagnostic accuracy of deep learning algorithms versus health-care …

[HTML][HTML] 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… - The Lancet Digital …, 2021 - thelancet.com
Health data that are publicly available are valuable resources for digital health research.
Several public datasets containing ophthalmological imaging have been frequently used in …

[HTML][HTML] Insights into systemic disease through retinal imaging-based oculomics

SK Wagner, DJ Fu, L Faes, X Liu… - … vision science & …, 2020 - tvst.arvojournals.org
Among the most noteworthy developments in ophthalmology over the last decade has been
the emergence of quantifiable high-resolution imaging modalities, which are typically non …

[HTML][HTML] A foundation model for generalizable disease detection from retinal images

Y Zhou, MA Chia, SK Wagner, MS Ayhan… - Nature, 2023 - nature.com
Medical artificial intelligence (AI) offers great potential for recognizing signs of health
conditions in retinal images and expediting the diagnosis of eye diseases and systemic …

[HTML][HTML] 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… - The Lancet Digital …, 2019 - thelancet.com
Background Deep learning has the potential to transform health care; however, substantial
expertise is required to train such models. We sought to evaluate the utility of automated …

[HTML][HTML] Code-free deep learning for multi-modality medical image classification

E Korot, Z Guan, D Ferraz, SK Wagner… - Nature Machine …, 2021 - nature.com
A number of large technology companies have created code-free cloud-based platforms that
allow researchers and clinicians without coding experience to create deep learning …

[HTML][HTML] Predicting sex from retinal fundus photographs using automated deep learning

E Korot, N Pontikos, X Liu, SK Wagner, L Faes… - Scientific reports, 2021 - nature.com
Deep learning may transform health care, but model development has largely been
dependent on availability of advanced technical expertise. Herein we present the …

Prevalence of Helicobacter pylori–associated gastritis in chronic urticaria

B Wedi, S Wagner, T Werfel, MP Manns… - International archives of …, 1998 - karger.com
Background: Chronic urticaria and concurrent angioedema are frustrating problems for both
physicians and patients. Methods: 100 patients with chronic urticaria (mean duration …

Bidirectional Ca2+ signaling occurs between the endoplasmic reticulum and acidic organelles

AJ Morgan, LC Davis, SKTY Wagner, AM Lewis… - Journal of Cell …, 2013 - rupress.org
The endoplasmic reticulum (ER) and acidic organelles (endo-lysosomes) act as separate
Ca2+ stores that release Ca2+ in response to the second messengers IP3 and cADPR (ER) …

[HTML][HTML] A clinician's guide to artificial intelligence: how to critically appraise machine learning studies

L Faes, X Liu, SK Wagner, DJ Fu… - … vision science & …, 2020 - tvst.arvojournals.org
In recent years, there has been considerable interest in the prospect of machine learning
models demonstrating expert-level diagnosis in multiple disease contexts. However, there is …