Study on predicting model for acute hypotensive episodes in ICU based on support vector machine.
- Author:
Lijuan LAI
1
;
Zhigang WANG
;
Xiaoming WU
;
Dongsheng XIONG
Author Information
1. Department of Biomedical Engineering, South China University of Technology, Guangzhou 510006, China.
- Publication Type:Journal Article
- MeSH:
Acute Disease;
Diagnosis, Computer-Assisted;
methods;
Forecasting;
Humans;
Hypotension;
diagnosis;
Intensive Care Units;
Models, Cardiovascular;
Support Vector Machine
- From:
Journal of Biomedical Engineering
2011;28(3):451-455
- CountryChina
- Language:Chinese
-
Abstract:
The occurrence of acute hypotensive episodes (AHE) in intensive care units (ICU) seriously endangers the lives of patients, and the treatment is mainly depended on the expert experience of doctors. In this paper, a model for predicting the occurrence of AHE in ICU has been developed using the theory of medical Informatics. We analyzed the trend and characteristics of the mean arterial blood pressure (MAP) between the patients who were suffering AHE and those who were not, and extracted the median, mean and other statistical parameters for learning and training based on support vector machine (SVM), then developed a predicting model. On this basis, we also compared different models consisted of different kernel functions. Experiments demonstrated that this approach performed well on classification and prediction, which would contribute to forecast the occurrence of AHE.
