COVID-19
As part of the effort research in the context of COVID-19, some of us have been involved at different levels in the analysis of both imaging and clinical data related to the COVID-19 pandemic.
In association with Zoe Global Limited, the Twinsuk team and other researchers from Massachusetts General Hospital and from Lund University, we participated in the analysis of the Covid Symptom study app, that gathers everyday reports from people across UK, US and Sweden about their symptoms. It allowed us to help modelling disease prevalence, incidence, study public health questions, investigate disease patterns or focus on specific populations of interest
In parallel, closer to our imaging core interest, we are involved with different hospitals, developing machine learning methods to allow introducing imaging features for better disease management.
Publications
Risk of COVID-19 among front-line health-care workers and the general community: a prospective cohort study
Nguyen, L.H., Drew, D.A., Graham, M.S., Joshi, A.D., Guo, C.G., Ma, W., Mehta, R.S., Warner, E.T., Sikavi, D.R., Lo, C.H. and Kwon, S., 2020. The Lancet Public Health.
Real-time tracking of self-reported symptoms to predict potential COVID-19
Menni, C., Valdes, A.M., Freidin, M.B., Sudre, C.H., Nguyen, L.H., Drew, D.A., Ganesh, S., Varsavsky, T., Cardoso, M.J., Moustafa, J.S.E.S. and Visconti, A., 2020. Nature medicine, pp.1-4.
Rapid implementation of mobile technology for real-time epidemiology of COVID-19
Drew, D.A., Nguyen, L.H., Steves, C.J., Menni, C., Freydin, M., Varsavsky, T., Sudre, C.H., Cardoso, M.J., Ourselin, S., Wolf, J. and Spector, T.D., 2020. Science.