Machine learning-based risk prediction of 28-day mortality for sepsis patients with augmented renal clearance

Yunzhe Wu; Fan Yang; Hongjie Yang; Tong Wu; RuoYu Zhuang; Xiaoli Wang; Yide Lu; Danfeng Dong

doi:10.1038/s41598-026-54630-w

Machine learning-based risk prediction of 28-day mortality for sepsis patients with augmented renal clearance

Y Yunzhe Wu F Fan Yang H Hongjie Yang T Tong Wu R RuoYu Zhuang X Xiaoli Wang (Center for Precision Environmental Health, Baylor College of Medicine, Houston, TX, USA.) Y Yide Lu D Danfeng Dong

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Article Details

Journal Scientific Reports

Volume / Issue Vol. 16, Issue 1

Published May 23, 2026

DOI 10.1038/s41598-026-54630-w

ISSN 2045-2322

Publisher Nature Portfolio

Journal Info

Scientific Reports

Nature Portfolio

ISSN: 2045-2322 Open Access Life Sciences

Authors (8)

Y

Yunzhe Wu

F

Fan Yang

H

Hongjie Yang

T

Tong Wu

R

RuoYu Zhuang

X

Xiaoli Wang

Center for Precision Environmental Health, Baylor College of Medicine, Houston, TX, USA.

Y

Yide Lu

D

Danfeng Dong

Machine learning-based risk prediction of 28-day mortality for sepsis patients with augmented renal clearance

Article Details

Journal Info

Authors (8)

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