| Rotation equivariant CNNs for digital pathology BS Veeling, J Linmans, J Winkens, T Cohen, M Welling Medical Image Computing and Computer Assisted Intervention–MICCAI 2018: 21st …, 2018 | 650 | 2018 |
| 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 | 267 | 2020 |
| Contrastive training for improved out-of-distribution detection J Winkens, R Bunel, AG Roy, R Stanforth, V Natarajan, JR Ledsam, ... arXiv preprint arXiv:2007.05566, 2020 | 258 | 2020 |
| Robust and data-efficient generalization of self-supervised machine learning for diagnostic imaging S Azizi, L Culp, J Freyberg, B Mustafa, S Baur, S Kornblith, T Chen, ... Nature Biomedical Engineering 7 (6), 756-779, 2023 | 141 | 2023 |
| Does your dermatology classifier know what it doesn’t know? detecting the long-tail of unseen conditions AG Roy, J Ren, S Azizi, A Loh, V Natarajan, B Mustafa, N Pawlowski, ... Medical Image Analysis 75, 102274, 2022 | 117 | 2022 |
| Supervised transfer learning at scale for medical imaging B Mustafa, A Loh, J Freyberg, P MacWilliams, M Wilson, SM McKinney, ... arXiv preprint arXiv:2101.05913, 2021 | 82 | 2021 |
| Robust and efficient medical imaging with self-supervision S Azizi, L Culp, J Freyberg, B Mustafa, S Baur, S Kornblith, T Chen, ... arXiv preprint arXiv:2205.09723, 2022 | 75 | 2022 |
| Enhancing the reliability and accuracy of AI-enabled diagnosis via complementarity-driven deferral to clinicians K Dvijotham, J Winkens, M Barsbey, S Ghaisas, R Stanforth, N Pawlowski, ... Nature Medicine 29 (7), 1814-1820, 2023 | 57 | 2023 |
| Sample efficient semantic segmentation using rotation equivariant convolutional networks J Linmans, J Winkens, BS Veeling, TS Cohen, M Welling arXiv preprint arXiv:1807.00583, 2018 | 26 | 2018 |
| Improved semantic segmentation for histopathology using rotation equivariant convolutional networks J Winkens, J Linmans, BS Veeling, TS Cohen, M Welling | 20 | 2018 |
| Predicting disease progression from tissue images and tissue segmentation maps J Yim, RK Chopra, T Spitz, JH Winkens, AAN Obika, T Back, JR Ledsam, ... US Patent 11,935,232, 2024 | 2 | 2024 |
| 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 | 1 | 2020 |
| Machine Learning Model for Detecting Out-Of-Distribution Inputs P MacWilliams, AG Roy, J Winkens, A Karthikesalingam, J Ren, ... US Patent App. 18/551,847, 2024 | | 2024 |
| Classifying out-of-distribution data using a contrastive loss R Bunel, JH Winkens, AG Roy, O Ronneberger, SM Eslami, AT Cemgil, ... US Patent App. 17/798,969, 2023 | | 2023 |
| 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 |
Joseph LedsamResearch Scientist, GoogleVerified email at google.com
