Data Sheet 1_Use of machine learning models to predict mortality in dialysis patients.pdf

Background<p>Mortality among maintenance hemodialysis patients remains high, and traditional statistical models often fail to capture complex clinical relationships. This study aimed to systematically develop, compare, and validate 19 machine learning algorithms for predicting all-cause mortal...

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Bibliographic Details
Main Author:	Junmin Huang (2431492) (author)
Other Authors:	Lu Chen (75170) (author), Hongying Luo (1579687) (author), Junhao Song (22786508) (author), Ziqian Bi (22786511) (author), Keyu Chen (6905702) (author), Xin Liang Chia (22786514) (author), Ming Liu (105953) (author), Tianyang Wang (2747137) (author), Benji Peng (22786517) (author), Zihan Wei (711352) (author), Zhiqing Huang (13720) (author), Zhihang Li (11978405) (author), Xincheng Liu (171940) (author), Hongjiu Zhou (22786520) (author), Weihuang Zhang (21248067) (author), Wen Wen (596162) (author), Mianna Luo (19234660) (author), Shujun Wang (432162) (author), Huafeng Liu (177955) (author), Chunjie Tian (607531) (author), Jibin Guan (4472794) (author), Joe Yeong (3760072) (author), Yongzhi Xu (15325396) (author), Peng Wang (34436) (author), Junfeng Hao (3202659) (author)
Published:	2025
Subjects:	Public Health and Health Services not elsewhere classified maintenance hemodialysis mortality prediction machine learning gradient boosting risk stratification
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Data Sheet 1_Use of machine learning models to predict mortality in dialysis patients.pdf

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