Identifying subtypes of chronic kidney disease with machine learning: development, internal validation and prognostic validation using linked electronic health records in 350,067 individuals
Mehrdad A Mizani
Jil B Mamza
Identifying Subtypes of Chronic Kidney Disease with Machine Learning: Development, Internal Validation and Prognostic Validation Using Electronic Health Records in 350067 Individuals
A retrospective cohort study measured predicting and validating the impact of the COVID-19 pandemic in individuals with chronic kidney disease.
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
Lifetime risk of cardiovascular-renal disease in type 2 diabetes: a population-based study in 473,399 individuals
Predicting and Validating Risk of Pre-Pandemic and Excess Mortality in Individuals With Chronic Kidney Disease