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지원벡터기계를 이용한 출혈을 일으킨 흰쥐에서의 생존 예측

Other Titles
 Survival Prediction of Rats with Hemorrhagic Shocks Using Support Vector Machine 
Authors
 장경환  ;  최재림  ;  유태근  ;  권민경  ;  김덕원 
Citation
 Journal of Biomedical Engineering Research (의공학회지), Vol.33(1) : 1-7, 2012 
Journal Title
 Journal of Biomedical Engineering Research  (의공학회지) 
ISSN
 1229-0807 
Issue Date
2012
Abstract
Hemorrhagic shock is a common cause of death in emergency rooms. Early diagnosis of hemorrhagic shock makes it possible for physicians to treat patients successfully. Therefore, the purpose of this study was to select an optimal survival prediction model using physiological parameters for the two analyzed periods: two and five minutes before and after the bleeding end. We obtained heart rates, mean arterial pressures, respiration rates and temperatures from 45 rats. These physiological parameters were used for the training and testing data sets of survival prediction models using an artificial neural network (ANN) and support vector machine (SVM). We applied a 5-fold cross validation method to avoid over-fitting and to select the optimal survival prediction model. In conclusion, SVM model showed slightly better accuracy than ANN model for survival prediction during the entire analysis period.
URI
https://ir.ymlib.yonsei.ac.kr/handle/22282913/92450
Appears in Collections:
1. Journal Papers (연구논문) > 1. College of Medicine (의과대학) > Dept. of Medical Engineering (의학공학교실)
Yonsei Authors
김덕원(Kim, Deok Won)
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