| Attributes and predictors of long COVID CH Sudre, B Murray, T Varsavsky, MS Graham, RS Penfold, RC Bowyer, ... Nature medicine 27 (4), 626-631, 2021 | 2769 | 2021 |
| Risk of COVID-19 among front-line health-care workers and the general community: a prospective cohort study LH Nguyen, DA Drew, MS Graham, AD Joshi, CG Guo, W Ma, RS Mehta, ... The Lancet Public Health 5 (9), e475-e483, 2020 | 2679 | 2020 |
| Real-time tracking of self-reported symptoms to predict potential COVID-19 C Menni, AM Valdes, MB Freidin, CH Sudre, LH Nguyen, DA Drew, ... Nature medicine 26 (7), 1037-1040, 2020 | 1558 | 2020 |
| Rapid implementation of mobile technology for real-time epidemiology of COVID-19 DA Drew, LH Nguyen, CJ Steves, C Menni, M Freydin, T Varsavsky, ... Science 368 (6497), 1362-1367, 2020 | 424 | 2020 |
| Changes in symptomatology, reinfection, and transmissibility associated with the SARS-CoV-2 variant B. 1.1. 7: an ecological study MS Graham, CH Sudre, A May, M Antonelli, B Murray, T Varsavsky, ... The Lancet Public Health 6 (5), e335-e345, 2021 | 394 | 2021 |
| Symptom clusters in COVID-19: A potential clinical prediction tool from the COVID Symptom Study app CH Sudre, KA Lee, M Ni Lochlainn, T Varsavsky, B Murray, MS Graham, ... Science advances 7 (12), eabd4177, 2021 | 220 | 2021 |
| Detecting COVID-19 infection hotspots in England using large-scale self-reported data from a mobile application: a prospective, observational study T Varsavsky, MS Graham, LS Canas, S Ganesh, JC Pujol, CH Sudre, ... The Lancet Public Health 6 (1), e21-e29, 2021 | 98 | 2021 |
| Cancer and risk of COVID‐19 through a general community survey KA Lee, W Ma, DR Sikavi, DA Drew, LH Nguyen, RCE Bowyer, ... The oncologist 26 (1), e182-e185, 2021 | 90 | 2021 |
| Test-time unsupervised domain adaptation T Varsavsky, M Orbes-Arteaga, CH Sudre, MS Graham, P Nachev, ... Medical Image Computing and Computer Assisted Intervention–MICCAI 2020: 23rd …, 2020 | 68 | 2020 |
| Automated Labelling using an Attention model for Radiology reports of MRI scans (ALARM) DA Wood, J Lynch, S Kafiabadi, E Guilhem, A Al Busaidi, A Montvila, ... Medical Imaging with Deep Learning, 811-826, 2020 | 47 | 2020 |
| Multi-domain Adaptation in Brain MRI Through Paired Consistency and Adversarial Learning M Orbes-Arteaga*, T Varsavsky*, CH Sudre, Z Eaton-Rosen, LJ Haddow, ... Domain Adaptation and Representation Transfer and Medical Image Learning …, 2019 | 45 | 2019 |
| A k-space model of movement artefacts: application to segmentation augmentation and artefact removal R Shaw, CH Sudre, T Varsavsky, S Ourselin, MJ Cardoso IEEE transactions on medical imaging 39 (9), 2881-2892, 2020 | 43 | 2020 |
| Knowledge barriers in a national symptomatic-COVID-19 testing programme MS Graham, A May, T Varsavsky, CH Sudre, B Murray, K Kläser, ... PLOS Global Public Health 2 (1), e0000028, 2022 | 32 | 2022 |
| Let’s agree to disagree: Learning highly debatable multirater labelling CH Sudre, BG Anson, S Ingala, CD Lane, D Jimenez, L Haider, ... Medical Image Computing and Computer Assisted Intervention–MICCAI 2019: 22nd …, 2019 | 29 | 2019 |
| PIMMS: permutation invariant multi-modal segmentation T Varsavsky, Z Eaton-Rosen, CH Sudre, P Nachev, MJ Cardoso Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical …, 2018 | 29 | 2018 |
| Geo-social gradients in predicted COVID-19 prevalence in Great Britain: results from 1 960 242 users of the COVID-19 Symptoms Study app RCE Bowyer, T Varsavsky, EJ Thompson, CH Sudre, BAK Murray, ... Thorax 76 (7), 723-725, 2021 | 27* | 2021 |
| Key predictors of attending hospital with COVID19: an association study from the COVID symptom Tracker APP in 2,618,948 individuals MN Lochlainn, KA Lee, CH Sudre, T Varsavsky, MJ Cardoso, C Menni, ... medRxiv, 2020.04. 25.20079251, 2020 | 27 | 2020 |
| 3D multirater RCNN for multimodal multi class segmentation of extremely small objects (ESO) CH Sudre, BG Anson, S Ingala, CD Lane, D Jimenez, L Haider, ... | 21* | |
| Neuromorphologicaly-preserving volumetric data encoding using VQ-VAE PD Tudosiu, T Varsavsky, R Shaw, M Graham, P Nachev, S Ourselin, ... arXiv preprint arXiv:2002.05692, 2020 | 20 | 2020 |
| Improved MR to CT synthesis for PET/MR attenuation correction using imitation learning K Kläser, T Varsavsky, P Markiewicz, T Vercauteren, D Atkinson, ... International Workshop on Simulation and Synthesis in Medical Imaging, 13-21, 2019 | 19 | 2019 |
M. Jorge CardosoReader, King's College LondonEmail confirmado em kcl.ac.uk
