Machine Learning Analysis of Time-Dependent Features for Predicting Adverse Events During Hemodialysis Therapy: Model Development and Validation Study

BACKGROUND: Hemodialysis (HD) therapy is an indispensable tool used in critical care management. Patients undergoing HD are at risk for intradialytic adverse events, ranging from muscle cramps to cardiac arrest. So far, there is no effective HD device–integrated algorithm to assist medical staff in...

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Detalles Bibliográficos
Autores principales: Liu, Yi-Shiuan, Yang, Chih-Yu, Chiu, Ping-Fang, Lin, Hui-Chu, Lo, Chung-Chuan, Lai, Alan Szu-Han, Chang, Chia-Chu, Lee, Oscar Kuang-Sheng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2021
Materias:
Original Paper
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8456349/
https://www.ncbi.nlm.nih.gov/pubmed/34491204
http://dx.doi.org/10.2196/27098

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8456349/
https://www.ncbi.nlm.nih.gov/pubmed/34491204
http://dx.doi.org/10.2196/27098

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