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Pos-201 Machine Learning Prediction of Imminent Dialysis in Advanced Ckd Patients

Year: 2022

Type: conference-abstract

Abstract: Timely education and preparation improve long-term outcomes and reduce healthcare costs for CKD patients who will ultimately progress to kidney failure. A predictive model able to accurately identify CKD patients in imminent need of kidney replacement therapy (KRT) would reduce the high morbidity and healthcare costs associated with unplanned dialysis.

Source: Kidney International Reports

DOI: 10.1016/j.ekir.2022.01.219

Authors: M. KLAMROWSKI, R. Klein, C.R. McCudden, J. Green, A. Molnar, G.L. Hundemer, A. Akbari

Institutions: Carleton University, University of Ottawa, McMaster University

Language: English

Topic: Dialysis and Renal Disease Management

Subfield: Nephrology

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $2,625

OpenAlex ID: W4212934579

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