(2023). Identifying subtypes of chronic kidney disease with machine learning: development, internal validation and prognostic validation using linked electronic health records in 350,067 individuals. Ebiomedicine, 89, 104489. http://doi.org/10.1016/j.ebiom.2023.104489.
(2022). Using national electronic health records for pandemic preparedness: validation of a parsimonious model for predicting excess deaths among those with COVID-19-a data-driven retrospective cohort study. J R Soc Med, 1410768221131897. http://doi.org/10.1177/01410768221131897.
(2018). Time spent at blood pressure target and the risk of death and cardiovascular diseases. PLoS One. http://doi.org/10.1371/journal.pone.0202359.
(2018). An electronic health records cohort study on heart failure following myocardial infarction in England: incidence and predictors. BMJ Open. http://doi.org/10.1136/bmjopen-2017-018331.
(2019). UK phenomics platform for developing and validating electronic health record phenotypes: CALIBER. J Am Med Inform Assoc. http://doi.org/10.1093/jamia/ocz105.
(2020). Obesity during the COVID-19 pandemic: both cause of high risk and potential effect of lockdown? A population-based electronic health record study. Public Health. http://doi.org/10.1016/j.puhe.2020.12.003.
(2020). Estimated impact of the COVID-19 pandemic on cancer services and excess 1-year mortality in people with cancer and multimorbidity: near real-time data on cancer care, cancer deaths and a population-based cohort study. BMJ Open. http://doi.org/10.1136/bmjopen-2020-043828.
(2020). Estimating excess 1-year mortality associated with the COVID-19 pandemic according to underlying conditions and age: a population-based cohort study. Lancet. http://doi.org/10.1016/s0140-6736(20)30854-0.
(2021). Excess deaths in people with cardiovascular diseases during the COVID-19 pandemic. Eur J Prev Cardiol. http://doi.org/10.1093/eurjpc/zwaa155.
(2021). Identifying adults at high-risk for change in weight and BMI in England: a longitudinal, large-scale, population-based cohort study using electronic health records. Lancet Diabetes Endocrinol. http://doi.org/10.1016/s2213-8587(21)00207-2.