Development and validation of a machine learning model to predict mortality risk in patients with COVID-19.

ABSTRACT: New York City quickly became an epicentre of the COVID-19 pandemic. An ability to triage patients was needed due to a sudden and massive increase in patients during the COVID-19 pandemic as healthcare providers incurred an exponential increase in workload,which created a strain on the staff and limited resources. Further, methods to better understand and characterise the predictors of morbidity and mortality was needed. METHODS: We developed a prediction model to predict patients at risk for mortality using only laboratory, vital and demographic information readily available in the electronic health record on more than 3395 hospital admissions with COVID-19. Multiple methods were applied, and final model was selected based on performance. A variable importance algorithm was used for interp

SUBMITTER: Stachel A 

PROVIDER: S-EPMC8108129 | biostudies-literature | 2021 May

REPOSITORIES: biostudies-literature