Articles avec mandats d'accès public - Trevor BackEn savoir plus
Disponibles quelque part : 14
International evaluation of an AI system for breast cancer screening
SM McKinney, M Sieniek, V Godbole, J Godwin, N Antropova, H Ashrafian, ...
Nature 577 (7788), 89-94, 2020
Exigences : Cancer Research UK, National Institute for Health Research, UK
Clinically applicable deep learning for diagnosis and referral in retinal disease
J De Fauw, JR Ledsam, B Romera-Paredes, S Nikolov, N Tomasev, ...
Nature medicine 24 (9), 1342-1350, 2018
Exigences : National Institute for Health Research, UK, Wellcome Trust
A clinically applicable approach to continuous prediction of future acute kidney injury
N Tomašev, X Glorot, JW Rae, M Zielinski, H Askham, A Saraiva, ...
Nature 572 (7767), 116-119, 2019
Exigences : US Department of Veterans Affairs, 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
Exigences : UK Medical Research Council, National Institute for Health Research, UK
Predicting conversion to wet age-related macular degeneration using deep learning
J Yim, R Chopra, T Spitz, J Winkens, A Obika, C Kelly, H Askham, M Lukic, ...
Nature Medicine 26 (6), 892-899, 2020
Exigences : UK Medical Research Council, National Institute for Health Research, UK
Clinically applicable segmentation of head and neck anatomy for radiotherapy: deep learning algorithm development and validation study
S Nikolov, S Blackwell, A Zverovitch, R Mendes, M Livne, J De Fauw, ...
Journal of medical Internet research 23 (7), e26151, 2021
Exigences : National Institute for Health Research, UK
Use of deep learning to develop continuous-risk models for adverse event prediction from electronic health records
N Tomašev, N Harris, S Baur, A Mottram, X Glorot, JW Rae, M Zielinski, ...
Nature Protocols 16 (6), 2765-2787, 2021
Exigences : National Institute for Health Research, UK
Automated analysis of retinal imaging using machine learning techniques for computer vision
J De Fauw, P Keane, N Tomasev, D Visentin, G van den Driessche, ...
F1000Research 5, 1573, 2017
Exigences : National Institute for Health Research, UK
Evaluation of a digitally-enabled care pathway for acute kidney injury management in hospital emergency admissions
A Connell, H Montgomery, P Martin, C Nightingale, O Sadeghi-Alavijeh, ...
NPJ digital medicine 2 (1), 67, 2019
Exigences : National Institute for Health Research, UK
Implementation of a digitally enabled care pathway (Part 2): qualitative analysis of experiences of health care professionals
A Connell, G Black, H Montgomery, P Martin, C Nightingale, D King, ...
Journal of Medical Internet Research 21 (7), e13143, 2019
Exigences : National Institute for Health Research, UK
Service evaluation of the implementation of a digitally-enabled care pathway for the recognition and management of acute kidney injury
A Connell, H Montgomery, S Morris, C Nightingale, S Stanley, M Emerson, ...
F1000Research 6, 1033, 2017
Exigences : National Institute for Health Research, UK
Implementation of a digitally enabled care pathway (part 1): impact on clinical outcomes and associated health care costs
A Connell, R Raine, P Martin, EC Barbosa, S Morris, C Nightingale, ...
Journal of medical Internet research 21 (7), e13147, 2019
Exigences : National Institute for Health Research, UK
Developing Deep Learning Continuous Risk Models for Early Adverse Event Prediction in Electronic Health Records: an AKI Case Study
N Tomašev, X Glorot, JW Rae, M Zielinski, H Askham, A Saraiva, ...
Exigences : US Department of Veterans Affairs, National Institute for Health Research, UK
digitally-enabled care pathway for the recognition and management of acute kidney injury [version 2; referees: 2
A Connell, H Montgomery, S Morris, C Nightingale, S Stanley, M Emerson, ...
Exigences : National Institute for Health Research, UK
Les informations concernant la publication et le financement sont déterminées automatiquement par un programme informatique