Evolutionary algorithms for multiobjective and multimodal optimization of diagnostic schemes

被引:7
|
作者
de Toro, F
Ros, E
Mota, S
Ortega, J
机构
[1] ETS Informat, Dept Signal Theory Telemat & Commun, Granada 18071, Spain
[2] Univ Granada, Dept Comp Architecture & Technol, Granada 18071, Spain
关键词
evolutionary algorithms; multiobjective and multimodal optimization; noninvasive medical diagnosis; paroxysmal atrial fibrillation;
D O I
10.1109/TBME.2005.862539
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
This paper addresses the optimization of noninvasive diagnostic schemes using evolutionary algorithms in medical applications based on the interpretation of biosignals. A general diagnostic methodology using a set of definable characteristics extracted from the biosignal source followed by the specific diagnostic scheme is presented. In this framework, multiobjective evolutionary algorithms are used to meet not only classification accuracy but also other objectives of medical interest, which can be conflicting. Furthermore, the use of both multimodal and multiobjective evolutionary optimization algorithms provides the medical specialist with different alternatives for configuring the diagnostic scheme. Some application examples of this methodology are described in the diagnosis of a specific cardiac disorder-paroxysmal atrial fibrillation.
引用
收藏
页码:178 / 189
页数:12
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