Ensemble learning approaches for early prediction of chronic kidney disease based on polysomnographic phenotype analysis

Abstract This study presents an ensemble learning approach for automated screening and severity classification of chronic kidney disease (CKD) using polysomnographic (PSG) phenotypes. We analyzed PSG data from 358 subjects (179 CKD, 179 early-CKD) in the Cleveland Family Study using four ensemble al...

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Autors principals:	Dong Hui Shin, Doljinsuren Enkhbayar, So Yeon Park, Jang Tae Gwan, Ha Young Park, Ji Ae Lee, Jae Won Yang, Jaesoo Kim, Erdenebayar Urtnasan
Format:	Artigo
Idioma:	Inglês
Publicat:	Nature Portfolio 2025-11-01
Col·lecció:	npj Digital Medicine
Accés en línia:	https://doi.org/10.1038/s41746-025-02039-6
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