Publications

(2024). Proteomic signatures improve risk prediction for common and rare diseases. Nat Med.

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(2024). Vaccinations, cardiovascular drugs, hospitalization, and mortality in COVID-19 and Long COVID. IJID.

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(2024). Automated Generation of Hospital Discharge Summaries Using Clinical Guidelines and Large Language Models. AAAI 2024 SSS on Clinical FMs.

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(2024). Ethnicity data resource in population-wide health records: completeness, coverage and granularity of diversity. Nature Scientific Data.

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(2023). Healthcare Utilisation of 282,080 Individuals with Long COVID Over Two Years: A Multiple Matched Control Cohort Analysis. SSRN.

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(2023). A nationwide study of 331 rare diseases among 58 million individuals: prevalence, demographics, and COVID-19 outcomes. medRxiv.

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(2023). Towards mitigating health inequity via machine learning: a nationwide cohort study to develop and validate ethnicity-specific models for prediction of cardiovascular disease risk in COVID-19 patients. medRxiv.

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(2023). Proteomic prediction of common and rare diseases. medRxiv.

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(2023). Hospital admissions linked to SARS-CoV-2 infection in children and adolescents: cohort study of 3.2 million first ascertained infections in England. BMJ.

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(2023). The impact of the COVID-19 pandemic on cardiovascular disease prevention and management. Nat Med.

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(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. JRSM.

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(2022). Digital ethnicity data in population-wide electronic health records in England: a description of completeness, coverage, and granularity of diversity. medRxiv.

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(2022). Association of COVID-19 With Major Arterial and Venous Thrombotic Diseases: A Population-Wide Cohort Study of 48 Million Adults in England and Wales. Circulation.

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(2022). Automating perfusion assessment of sublingual microcirculation in critical illness.

DOI

(2022). COVID-19 trajectories among 57 million adults in England: a cohort study using electronic health records. Lancet Digital Health.

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(2022). Evaluation of antithrombotic use and COVID-19 outcomes in a nationwide atrial fibrillation cohort. Heart.

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(2022). Using national electronic health records for pandemic preparedness: validation of a parsimonious model for predicting excess deaths among those with COVID-19. SSRN.

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(2022). The adverse impact of COVID-19 pandemic on cardiovascular disease prevention and management in England, Scotland and Wales: A population-scale descriptive analysis of trends in medication data. medRxiv.

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(2021). A nationwide deep learning pipeline to predict stroke and COVID-19 death in atrial fibrillation. medRxiv.

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(2021). Association of COVID-19 with arterial and venous vascular diseases: a population-wide cohort study of 48 million adults in England and Wales. medRxiv.

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(2021). Understanding COVID-19 trajectories from a nationwide linked electronic health record cohort of 56 million people: phenotypes, severity, waves & vaccination. medRxiv.

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(2021). Vaccinating adolescents against SARS-CoV-2 in England: a risk–benefit analysis. JRSM.

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(2021). Evaluation of antithrombotic use and COVID-19 outcomes in a nationwide atrial fibrillation cohort. medRxiv.

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(2021). Vaccinating adolescents in England: a risk-benefit analysis. OSF Preprints.

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(2021). Linked electronic health records for research on a nationwide cohort of more than 54 million people in England: data resource. BMJ.

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(2020). ‘Shielded’ anaesthetists and intensivists during the COVID‐19 pandemic. Anaesthesia.

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