Diagnosis of atherosclerosis from carotid artery Doppler signals as a real-world medical application of artificial immune systems

In this study, we have employed the maximum envelope of the carotid artery Doppler sonograms derived from Fast Fourier Transformation-Welch Method and artificial immune systems in order to distinguish between atherosclerosis and healthy subjects. In this classification problem, the used artificial immune system has reached to 99.33% classification accuracy using 10-fold Cross Validation (CV) method with only two system units which reduced classification time considerably. This success shows that whereas artificial immune systems is a new research area, one can utilize from this new field to reach high performance for his problem.