de Toro Francisco, Ros Eduardo, Mota Sonia, Ortega Julio
Department of Signal Theory, Telematics and Communications, ETS Informática, Granada, Spain.
IEEE Trans Biomed Eng. 2006 Feb;53(2):178-89. doi: 10.1109/TBME.2005.862539.
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.
本文探讨了在基于生物信号解读的医学应用中,使用进化算法优化非侵入性诊断方案的问题。提出了一种通用的诊断方法,该方法先从生物信号源提取一组可定义的特征,然后采用特定的诊断方案。在此框架下,多目标进化算法不仅用于满足分类准确性,还用于满足其他医学相关目标,而这些目标可能相互冲突。此外,多模态和多目标进化优化算法的使用为医学专家提供了配置诊断方案的不同选择。本文还描述了该方法在特定心脏疾病——阵发性心房颤动诊断中的一些应用实例。