Predicting mortality risk of COVID-19 among chronic kidney disease patients using machine learning algorithms

XG-Boost demonstrated predictive merit that can be leveraged as an auxiliary tool to aid clinicians in making more informed decisions in clinical settings.

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Publication Details

Journal
Health Informatics Journal
Published
2026-04-01
DOI
https://doi.org/10.1177/14604582261425071
Primary Topic
Machine Learning in Healthcare
Type
article
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article

Predicting mortality risk of COVID-19 among chronic kidney disease patients using machine learning algorithms

Raoof Nopour
Health Informatics Journal
Machine Learning in Healthcare
article

Predicting mortality risk of COVID-19 among chronic kidney disease patients using machine learning algorithms

Raoof Nopour
article en

Abstract

XG-Boost demonstrated predictive merit that can be leveraged as an auxiliary tool to aid clinicians in making more informed decisions in clinical settings.

Health Informatics JournalVol. 32(2)
Iran University of Medical Sciences (IR), Health Information Management (BE)
Good health and well-being
Openalex Percentile: Top 32%
Machine Learning in Healthcare
DOIOpen Access PDFOpenAlex
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