Denaxas Lab
Denaxas Lab
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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
A retrospective cohort study predicting and validating impact of the COVID-19 pandemic in individuals with chronic kidney
Identifying Subtypes of Chronic Kidney Disease with Machine Learning: Development, Internal Validation and Prognostic Validation Using Electronic Health Records in 350067 Individuals
A Complex Systems Perspective on Macroprudential Regulation.
Using National Electronic Health Records for Pandemic Preparedness: Validation of a Parsimonious Model for Predicting Excess Deaths Among Those With COVID-19
Observational retrospective study examining health service costs of patients receiving surgery for chronic rhinosinusitis in England, using linked primary and secondary care electronic patient-level data
Predicting and Validating Risk of Pre-Pandemic and Excess Mortality in Individuals With Chronic Kidney Disease
UK phenomics platform for developing and validating EHR phenotypes: CALIBER
A population-based study of 92 clinically recognized risk factors for heart failure: co-occurrence, prognosis and preventive potential
A retrospective cohort study measured predicting and validating the impact of the COVID-19 pandemic in individuals with chronic kidney disease.
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