Machine Learning for Prediction of Patients on Hemodialysis with an Undetected SARS-CoV-2 Infection
Abstract
We developed a machine learning (ML) model that predicts the risk of a patient on hemodialysis (HD) having an undetected SARS-CoV-2 infection that is identified after the following ≥3 days.As part of a healthcare operations effort, we used patient data from a national network of dialysis clinics (February-September 2020) to develop an ML model (XGBoost) that uses 81 variables to predict the likelihood of an adult patient on HD having an...
Paper Details
Title
Machine Learning for Prediction of Patients on Hemodialysis with an Undetected SARS-CoV-2 Infection
Published Date
Mar 1, 2021
Journal
Volume
2
Issue
3
Pages
456 - 468
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