Construction and application of machine learning models for predicting intradialytic hypotension

Machine learning emerged as a reliable tool for predicting IDH in HD patients. Notably, LVMI emerged as a crucial feature for effectively predicting IDH. The simplified models are accessible on the provided website.

Authors

Institutions

Publication Details

Journal
PLoS ONE
Published
2025-10-08
DOI
https://doi.org/10.1371/journal.pone.0333357
Citations
2
Primary Topic
Hemodynamic Monitoring and Therapy
Type
article
Field-Weighted Citation Impact
4.01
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Construction and application of machine learning models for predicting intradialytic hypotension

Kedan Cai, Zhijian Ren, Qun Luo, Ningjie Xu et al.
2 citations
PLoS ONE
Hemodynamic Monitoring and Therapy
4.01
article

Construction and application of machine learning models for predicting intradialytic hypotension

Kedan Cai, Zhijian Ren, Qun Luo, Ningjie Xu, Pingping Wang, Yihui Qu, Yue Hong, Lingping Wu
article en
2 citations

Abstract

Machine learning emerged as a reliable tool for predicting IDH in HD patients. Notably, LVMI emerged as a crucial feature for effectively predicting IDH. The simplified models are accessible on the provided website.

PLoS ONEVol. 20(10)
Ningbo University (CN), Ningbo No. 2 Hospital (CN), Ningbo No.6 Hospital (CN)
Openalex Percentile: Top 6%
Hemodynamic Monitoring and Therapy
4.01
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.