Title :
Evolutionary algorithms for multiobjective and multimodal optimization of diagnostic schemes
Author :
De Toro, Francisco ; Ros, Eduardo ; Mota, Sonia ; Ortega, Julio
Author_Institution :
Dept. of Signal Theor., E.T.S. Informatica, Granada, Spain
Abstract :
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.
Keywords :
bioelectric phenomena; cardiology; evolutionary computation; medical signal processing; optimisation; patient diagnosis; signal classification; biosignal classification; cardiac disorder-paroxysmal atrial fibrillation; evolutionary algorithms; medical applications; multimodal optimization; multiobjective optimization; noninvasive Diagnostic Schemes; Atrial fibrillation; Biomedical equipment; Computer architecture; Constraint optimization; Electronic mail; Evolutionary computation; Medical diagnosis; Medical diagnostic imaging; Medical services; Telematics; Evolutionary algorithms; multiobjective and multimodal optimization; noninvasive medical diagnosis; paroxysmal atrial fibrillation; Algorithms; Artificial Intelligence; Atrial Fibrillation; Computer Simulation; Decision Support Systems, Clinical; Decision Support Techniques; Diagnosis, Computer-Assisted; Electrocardiography; Factor Analysis, Statistical; Humans; Models, Biological; Pattern Recognition, Automated; Reproducibility of Results; Sensitivity and Specificity;
Journal_Title :
Biomedical Engineering, IEEE Transactions on
DOI :
10.1109/TBME.2005.862539