User profiles for "author:Siegfried Wagner"
Siegfried WagnerUniversity 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 …
Background Deep learning offers considerable promise for medical diagnostics. We aimed
to evaluate the diagnostic accuracy of deep learning algorithms versus health-care …
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
Health data that are publicly available are valuable resources for digital health research.
Several public datasets containing ophthalmological imaging have been frequently used in …
Several public datasets containing ophthalmological imaging have been frequently used in …
[HTML][HTML] Insights into systemic disease through retinal imaging-based oculomics
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 …
the emergence of quantifiable high-resolution imaging modalities, which are typically non …
[HTML][HTML] A foundation model for generalizable disease detection from retinal images
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 …
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
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 …
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
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 …
allow researchers and clinicians without coding experience to create deep learning …
[HTML][HTML] Predicting sex from retinal fundus photographs using automated deep learning
Deep learning may transform health care, but model development has largely been
dependent on availability of advanced technical expertise. Herein we present the …
dependent on availability of advanced technical expertise. Herein we present the …
Prevalence of Helicobacter pylori–associated gastritis in chronic urticaria
Background: Chronic urticaria and concurrent angioedema are frustrating problems for both
physicians and patients. Methods: 100 patients with chronic urticaria (mean duration …
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) …
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
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 …
models demonstrating expert-level diagnosis in multiple disease contexts. However, there is …