Research progress on identification of acute respiratory distress syndrome based on noninvasive parameters
10.7687/j.issn1003-8868.2018.04.092
- VernacularTitle:基于无创参数辨识急性呼吸窘迫综合征的相关算法研究进展
- Author:
Peng-Cheng YANG
1
;
Guang ZHANG
;
Feng CHEN
;
Ming YU
;
Chun-Chen WANG
;
Tai-Hu WU
Author Information
1. 军事科学院系统工程研究院卫勤保障技术研究所
- Keywords:
acute respiratory distress syndrome;
acute lung injury;
noninvasive parameter;
regression method;
nonlinear fit-ting method;
multi parameter method
- From:
Chinese Medical Equipment Journal
2018;39(4):92-96,106
- CountryChina
- Language:Chinese
-
Abstract:
The concept and pathogenesis of acute respiratory distress syndrome (ARDS)were introduced,and the methods for identifying ARDS based on noninvasive parameters in recent years were retrospectively reviewed including regression method, nonlinear fitting method and multi parameter method.The above methods had their advantages and disadvantages summarized. It's suggested that multi noninvasive parameters and machine learning algorithms such as neural network, support vector machine and decision tree be involved in model construction to promote PaO2/FiO2assessment based on noninvasive parameters,so that the rapid diagnosis and real-time monitoring of ARDS can be realized based on noninvasive parameters while there were no need for blood gas analysis.
