(2023). Temporal trends of cause-specific mortality after diagnosis of atrial fibrillation. Eur Heart J. http://doi.org/10.1093/eurheartj/ehad571.
(2023). Prognosis, characteristics, and provision of care for patients with the unspecified heart failure electronic health record phenotype: a population-based linked cohort study of 95262 individuals. Eclinicalmedicine, 63, 102164. http://doi.org/10.1016/j.eclinm.2023.102164.
(2023). Incident cardiovascular, renal, metabolic diseases and death in individuals identified for risk-guided atrial fibrillation screening: a nationwide cohort study. Open Heart, 10. http://doi.org/10.1136/openhrt-2023-002357.
(2023). Prediction of short-term atrial fibrillation risk using primary care electronic health records. Heart. http://doi.org/10.1136/heartjnl-2022-322076.
(2022). Temporal trends and patterns in atrial fibrillation incidence: A population-based study of 3·4 million individuals. Lancet Reg Health Eur, 17, 100386. http://doi.org/10.1016/j.lanepe.2022.100386.
(2020). Glucocorticoid dose-dependent risk of type 2 diabetes in six immune-mediated inflammatory diseases: a population-based cohort analysis. BMJ Open Diabetes Res Care. http://doi.org/10.1136/bmjdrc-2020-001220.
(2020). Dose-dependent oral glucocorticoid cardiovascular risks in people with immune-mediated inflammatory diseases: A population-based cohort study. PLoS Med. http://doi.org/10.1371/journal.pmed.1003432.
(2021). Predicting patient-level new-onset atrial fibrillation from population-based nationwide electronic health records: protocol of FIND-AF for developing a precision medicine prediction model using artificial intelligence. BMJ Open. http://doi.org/10.1136/bmjopen-2021-052887.