Thomas Varsavsky
Thomas Varsavsky
University College London and King's College London
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Cited by
Cited by
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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, ...
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