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Deep Learning Model for Predicting Intradialytic Hypotension Without Privacy Infringement: A Retrospective Two-Center Study

Authors :
Hyung Woo Kim
Seok-Jae Heo
Minseok Kim
Jakyung Lee
Keun Hyung Park
Gongmyung Lee
Song In Baeg
Young Eun Kwon
Hye Min Choi
Dong-Jin Oh
Chung-Mo Nam
Beom Seok Kim
Source :
Frontiers in Medicine, Vol 9 (2022)
Publication Year :
2022
Publisher :
Frontiers Media S.A., 2022.

Abstract

ObjectivePreviously developed Intradialytic hypotension (IDH) prediction models utilize clinical variables with potential privacy protection issues. We developed an IDH prediction model using minimal variables, without the risk of privacy infringement.MethodsUnidentifiable data from 63,640 hemodialysis sessions (26,746 of 79 patients for internal validation, 36,894 of 255 patients for external validation) from two Korean hospital hemodialysis databases were finally analyzed, using three IDH definitions: (1) systolic blood pressure (SBP) nadir

Details

Language :
English
ISSN :
2296858X
Volume :
9
Database :
Directory of Open Access Journals
Journal :
Frontiers in Medicine
Publication Type :
Academic Journal
Accession number :
edsdoj.8faa5780f14a449b84d3f4e7b0d612a3
Document Type :
article
Full Text :
https://doi.org/10.3389/fmed.2022.878858