| 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 | 885 | 2018 |
| 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 | 412 | 2020 |
| Lasagne: first release S Dieleman, J Schlüter, C Raffel, E Olson, SK Sønderby, D Nouri, ... Zenodo: Geneva, Switzerland 3, 74, 2015 | 398* | 2015 |
| Data-Efficient Image Recognition with Contrastive Predictive Coding OJ Hénaff, A Srinivas, JD Fauw, A Razavi, C Doersch, SMA Eslami, ... | 278 | 2020 |
| Exploiting cyclic symmetry in convolutional neural networks S Dieleman, J De Fauw, K Kavukcuoglu International conference on machine learning, 1889-1898, 2016 | 218 | 2016 |
| A probabilistic u-net for segmentation of ambiguous images SAA Kohl, B Romera-Paredes, C Meyer, J De Fauw, JR Ledsam, ... arXiv preprint arXiv:1806.05034, 2018 | 162 | 2018 |
| Deep learning to achieve clinically applicable segmentation of head and neck anatomy for radiotherapy S Nikolov, S Blackwell, R Mendes, J De Fauw, C Meyer, C Hughes, ... arXiv preprint arXiv:1809.04430, 2018 | 110 | 2018 |
| 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 | 41 | 2016 |
| 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 | 21 | 2016 |
| 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 | 20 | 2020 |
| 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 | 15 | 2020 |
| Hierarchical autoregressive image models with auxiliary decoders J De Fauw, S Dieleman, K Simonyan arXiv preprint arXiv:1903.04933, 2019 | 15 | 2019 |
| 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 | 6 | 2019 |
| Self-supervised multimodal versatile networks JB Alayrac, A Recasens, R Schneider, R Arandjelović, J Ramapuram, ... arXiv preprint arXiv:2006.16228, 2020 | 3 | 2020 |
| Addendum: International evaluation of an AI system for breast cancer screening SM McKinney, M Sieniek, V Godbole, J Godwin, N Antropova, H Ashrafian, ... Nature 586 (7829), E19-E19, 2020 | 2 | 2020 |
| Generalizable medical image analysis using segmentation and classification neural networks J De Fauw, JR Ledsam, B Romera-Paredes, S Nikolov, N Tomasev, ... US Patent 10,878,601, 2020 | | 2020 |
| 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 |
| 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 | | 2020 |
| 3-d convolutional neural networks for organ segmentation in medical images for radiotherapy planning S Nikolov, S Blackwell, J De Fauw, B Romera-Paredes, C Meyer, ... US Patent App. 16/565,384, 2020 | | 2020 |
Sander DielemanResearch Scientist, DeepMindVerified email at google.com
Sander DielemanResearch Scientist, DeepMindVerified email at google.com