Back to Search Start Over

Dose Regulation Model of Norepinephrine Based on LSTM Network and Clustering Analysis in Sepsis

Authors :
Jingming Liu
Minghui Gong
Wei Guo
Chunping Li
Hui Wang
Shuai Zhang
Christopher Nugent
Source :
International Journal of Computational Intelligence Systems, Vol 13, Iss 1 (2020)
Publication Year :
2020
Publisher :
Springer, 2020.

Abstract

Sepsis is a life-threatening condition that arises when the body's response to infection causes injury to its own tissues and organs. Despite the advancement of medical diagnosis and treatment technologies, the morbidity and mortality of sepsis are still relatively high. In this paper, a two-layer long short-term memory (LSTM) model is proposed to predict the dose of norepinephrine, in order to control the blood pressure of patients. The proposed modeling approach is evaluated using the MIMIC-III dataset, achieving higher performance.

Details

Language :
English
ISSN :
18756883
Volume :
13
Issue :
1
Database :
Directory of Open Access Journals
Journal :
International Journal of Computational Intelligence Systems
Publication Type :
Academic Journal
Accession number :
edsdoj.52d69c3f31fb4a938327cea9ab5e9805
Document Type :
article
Full Text :
https://doi.org/10.2991/ijcis.d.200512.001