COMPARISON BETWEEN SVM AND ANN FOR MODELING THE CEREBRAL AUTOREGULATION BLOOD FLOW SYSTEM

被引：0

作者：

Chacon, Max ^{[1
]}

Araya, Claudio ^{[1
]}

Munoz, Marcela ^{[1
]}

Panerai, Ronney B. ^{[2
]}

机构：

[1] Univ Santiago Chile, Dept Informat, Av Ecuador 3659, Santiago, Chile

[2] Univ Leicester, Dept Cardiovasc Sci, Leicester LE1 5WW, Leics, England

来源：

IJCCI 2009: PROCEEDINGS OF THE INTERNATIONAL JOINT CONFERENCE ON COMPUTATIONAL INTELLIGENCE | 2009年

关键词：

Support vector machine; Artificial neural networks; Cerebral blood flow autoregulation; SUPPORT VECTOR MACHINES; IDENTIFICATION; HUMANS;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The performance of SVMs and ANNs as identifiers of time systems is compared with the purpose of analyzing the Cerebral blood flow Autoregulation System, one of the main systems in the field of cerebral hemodynamics. The main variables of this system are Arterial Blood Pressure (ABP) variations and changes in End-tidal pCO(2) (EtCO2). In this work we show that models that have ABP and EtCO2 as input, trained with the SVM, are superior to ANN models in terms of the fit of an unknown set, and they are also more adequate for measuring the influence of EtCO2 on Cerebral Blood Flow Velocity.

引用

页码：522 / +

页数：2

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