2024
DOI: 10.1038/s41598-024-52251-9
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Predicting CKD progression using time-series clustering and light gradient boosting machines

Hirotaka Saito,
Hiroki Yoshimura,
Kenichi Tanaka
et al.

Abstract: Predicting the transition of kidney function in chronic kidney disease is difficult as specific symptoms are lacking and often overlooked, and progress occurs due to complicating factors. In this study, we applied time-series cluster analysis and a light gradient boosting machine to predict the trajectories of kidney function in non-dialysis dependent chronic kidney disease patients with baseline estimated glomerular filtration rate (GFR) ≥ 45 mL/min/1.73 m2. Based on 5-year changes in estimated GFR, participa… Show more

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Cited by 2 publications
(1 citation statement)
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“…The Fukushima CKD Cohort study, a sub-cohort of the Fukushima Cohort study [8][9][10][11][12][13] , is a prospective survey of patient characteristics and outcomes for participants with non-dialysis-dependent CKD being followed at the Fukushima Medical University Hospital (Fukushima Prefecture, northeastern area of Japan). A total of 2,724 patients were enrolled in the Fukushima Cohort study, of whom patients with…”
Section: Study Populationmentioning
confidence: 99%
“…The Fukushima CKD Cohort study, a sub-cohort of the Fukushima Cohort study [8][9][10][11][12][13] , is a prospective survey of patient characteristics and outcomes for participants with non-dialysis-dependent CKD being followed at the Fukushima Medical University Hospital (Fukushima Prefecture, northeastern area of Japan). A total of 2,724 patients were enrolled in the Fukushima Cohort study, of whom patients with…”
Section: Study Populationmentioning
confidence: 99%