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Predicting Acute Kidney Injury: A Machine Learning...
Journal article

Predicting Acute Kidney Injury: A Machine Learning Approach Using Electronic Health Records

Abstract

Acute kidney injury (AKI) is a common complication in hospitalized patients and can result in increased hospital stay, health-related costs, mortality and morbidity. A number of recent studies have shown that AKI is predictable and avoidable if early risk factors can be identified by analyzing Electronic Health Records (EHRs). In this study, we employ machine learning techniques to identify older patients who have a risk of readmission with AKI …

Authors

Abdullah SS; Rostamzadeh N; Sedig K; Garg AX; McArthur E

Journal

Information, Vol. 11, No. 8,

Publisher

MDPI

DOI

10.3390/info11080386

ISSN

2078-2489

Labels

Sustainable Development Goals (SDG)