First experiences with machine learning predictions of accelerated declining eGFR slope of living kidney donors 3 years after donation
Leandra Lukomski,
Juan Pisula,
Tristan Wagner
et al.
Abstract:Background
Living kidney donors are screened pre-donation to estimate the risk of end-stage kidney disease (ESKD). We evaluate Machine Learning (ML) to predict the progression of kidney function deterioration over time using the estimated GFR (eGFR) slope as the target variable.
Methods
We included 238 living kidney donors who underwent donor nephrectomy. We divided the dataset based on the eGFR slope in the third follow-up year, resulting in 185 donors wi… Show more
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