Prediction of susceptibility to acute mountain sickness based on LVQ neural-network model
10.11659/jjssx.08E015149
- VernacularTitle:急性高原病易感性LVQ神经网络模型预测研究
- Author:
Haiyan YOU
;
Yuqi GAO
;
Zhaohui HUANG
- Publication Type:Journal Article
- Keywords:
acute mountain sickness;
susceptibility;
LVQ neural-network model;
prediction
- From:
Journal of Regional Anatomy and Operative Surgery
2015;24(6):627-629
- CountryChina
- Language:Chinese
-
Abstract:
Objective The purpose of this study was to examine the relationship between acute mountain sickness ( AMS) and AMS susceptibility indices before ascent to high altitude and to evaluate their predictive value for AMS. Methods A total of 314 healthy male a-dults were voluntarily enrolled. Their 22 physiological and mental indices of AMS susceptibility were obtained before exposure high altitude. The diagnoses of AMS were based on the Lake Louise score ( LLS) ,an international standard scoring system for AMS. According to the char-acteristics of selected AMS susceptibility indices and the strong fault tolerance of neural network theory, the learning vector quantization ( LVQ) neural network method was adopted to build the prediction model of susceptibility to AMS. Results The results showed the sensitiv-ity of the LVQ model which distinguishes subjects with no-AMS reached 95. 00%,the average correct-prediction precision ultimately reached 72. 22%. The result of prediction is believable. Conclusion The builded LVQ model provide a scientific method for screening crowd who quickly ascend to high altitude,and also can lead to an effective preliminary screening of susceptibility to AMS.
