Predicting and Validating Risk of Pre-Pandemic and Excess Mortality in Individuals With Chronic Kidney Disease
Mehrdad A Mizani
Jil Billy Mamza
A retrospective cohort study measured predicting and validating the impact of the COVID-19 pandemic in individuals with chronic kidney disease.
Identifying Subtypes of Chronic Kidney Disease with Machine Learning: Development, Internal Validation and Prognostic Validation Using Electronic Health Records in 350067 Individuals
Using National Electronic Health Records for Pandemic Preparedness: Validation of a Parsimonious Model for Predicting Excess Deaths Among Those With COVID-19
Identifying subtypes of chronic kidney disease with machine learning: development, internal validation and prognostic validation using linked electronic health records in 350,067 individuals
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