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Jeffrey De Fauw
Jeffrey De Fauw
Unknown affiliation
Verified email at defauw.ai - Homepage
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Cited by
Year
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
14192018
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
11102020
Data-Efficient Image Recognition with Contrastive Predictive Coding
OJ Hénaff, A Srinivas, JD Fauw, A Razavi, C Doersch, SMA Eslami, ...
7212020
Lasagne: first release
S Dieleman, J Schlüter, C Raffel, E Olson, SK Sønderby, D Nouri, ...
Zenodo: Geneva, Switzerland 3, 74, 2015
424*2015
Exploiting cyclic symmetry in convolutional neural networks
S Dieleman, J De Fauw, K Kavukcuoglu
International conference on machine learning, 1889-1898, 2016
3002016
A probabilistic u-net for segmentation of ambiguous images
S Kohl, B Romera-Paredes, C Meyer, J De Fauw, JR Ledsam, ...
Advances in neural information processing systems 31, 2018
2882018
Deep learning to achieve clinically applicable segmentation of head and neck anatomy for radiotherapy
S Nikolov, S Blackwell, A Zverovitch, R Mendes, M Livne, J De Fauw, ...
arXiv preprint arXiv:1809.04430, 2018
1872018
Self-supervised multimodal versatile networks
JB Alayrac, A Recasens, R Schneider, R Arandjelović, J Ramapuram, ...
Advances in Neural Information Processing Systems 33, 25-37, 2020
1292020
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
1012020
Developing specific reporting guidelines for diagnostic accuracy studies assessing AI interventions: The STARD-AI Steering Group
V Sounderajah, H Ashrafian, R Aggarwal, J De Fauw, AK Denniston, ...
Nature medicine 26 (6), 807-808, 2020
962020
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, 2016
512016
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
272021
Applying machine learning to automated segmentation of head and neck tumour volumes and organs at risk on radiotherapy planning CT and MRI scans
C Chu, J De Fauw, N Tomasev, BR Paredes, C Hughes, J Ledsam, ...
F1000Research 5 (2104), 2104, 2016
252016
Hierarchical autoregressive image models with auxiliary decoders
J De Fauw, S Dieleman, K Simonyan
arXiv preprint arXiv:1903.04933, 2019
222019
Generalizable medical image analysis using segmentation and classification neural networks
J De Fauw, JR Ledsam, B Romera-Paredes, S Nikolov, N Tomasev, ...
US Patent 10,198,832, 2019
192019
Developing a reporting guideline for artificial intelligence-centred diagnostic test accuracy studies: the STARD-AI protocol
V Sounderajah, H Ashrafian, RM Golub, S Shetty, J De Fauw, L Hooft, ...
BMJ open 11 (6), e047709, 2021
122021
3-D convolutional neural networks for organ segmentation in medical images for radiotherapy planning
S Nikolov, S Blackwell, J De Fauw, B Romera-Paredes, CL Meyer, ...
US Patent 11,100,647, 2021
12021
Quantitative analysis of change in retinal tissues in neovascular age-related macular degeneration using artificial intelligence
R Chopra, G Moraes, DJ Fu, S Wagner, T Spitz, M Wilson, J Yim, ...
Investigative Ophthalmology & Visual Science 61 (7), 1152-1152, 2020
12020
Automatic segmentation using artificial intelligence of baseline anatomical parameters of patients starting anti-VEGF injections for neovascular age-related macular degeneration
G Moraes, R Chopra, DJ Fu, S Wagner, T Spitz, M Wilson, J Yim, ...
Investigative Ophthalmology & Visual Science 61 (7), 1633-1633, 2020
2020
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