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지원벡터기계를 이용한 출혈을 일으킨 흰쥐에서의 생존 예측
DC Field | Value | Language |
---|---|---|
dc.contributor.author | 김덕원 | - |
dc.date.accessioned | 2014-12-19T17:59:43Z | - |
dc.date.available | 2014-12-19T17:59:43Z | - |
dc.date.issued | 2012 | - |
dc.identifier.issn | 1229-0807 | - |
dc.identifier.uri | https://ir.ymlib.yonsei.ac.kr/handle/22282913/92450 | - |
dc.description.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. | - |
dc.description.statementOfResponsibility | open | - |
dc.format.extent | 1~7 | - |
dc.relation.isPartOf | Journal of Biomedical Engineering Research (의공학회지) | - |
dc.rights | CC BY-NC-ND 2.0 KR | - |
dc.rights.uri | https://creativecommons.org/licenses/by-nc-nd/2.0/kr/ | - |
dc.title | 지원벡터기계를 이용한 출혈을 일으킨 흰쥐에서의 생존 예측 | - |
dc.title.alternative | Survival Prediction of Rats with Hemorrhagic Shocks Using Support Vector Machine | - |
dc.type | Article | - |
dc.contributor.college | College of Medicine (의과대학) | - |
dc.contributor.department | Dept. of Medical Engineering (의학공학) | - |
dc.contributor.googleauthor | 장경환 | - |
dc.contributor.googleauthor | 최재림 | - |
dc.contributor.googleauthor | 유태근 | - |
dc.contributor.googleauthor | 권민경 | - |
dc.contributor.googleauthor | 김덕원 | - |
dc.admin.author | false | - |
dc.admin.mapping | false | - |
dc.contributor.localId | A00376 | - |
dc.relation.journalcode | J01263 | - |
dc.identifier.pmid | hemorrhagic shock ; artificial neural network ; support vector machine ; 5-fold cross validation ; survival prediction | - |
dc.subject.keyword | hemorrhagic shock | - |
dc.subject.keyword | artificial neural network | - |
dc.subject.keyword | support vector machine | - |
dc.subject.keyword | 5-fold cross validation | - |
dc.subject.keyword | survival prediction | - |
dc.contributor.alternativeName | Kim, Deok Won | - |
dc.contributor.affiliatedAuthor | Kim, Deok Won | - |
dc.citation.volume | 33 | - |
dc.citation.number | 1 | - |
dc.citation.startPage | 1 | - |
dc.citation.endPage | 7 | - |
dc.identifier.bibliographicCitation | Journal of Biomedical Engineering Research (의공학회지), Vol.33(1) : 1-7, 2012 | - |
dc.identifier.rimsid | 31334 | - |
dc.type.rims | ART | - |
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