Title | ||
---|---|---|
Diagnosis of atherosclerosis from carotid artery Doppler signals as a real-world medical application of artificial immune systems |
Abstract | ||
---|---|---|
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. |
Year | DOI | Venue |
---|---|---|
2007 | 10.1016/j.eswa.2006.05.034 | Expert Syst. Appl. |
Keywords | Field | DocType |
atherosclerosis,classification time,welch,carotid artery doppler signal,carotid artery,fast fourier transformation,classification accuracy,system unit,fast fourier transformation-welch method,new research area,new field,10-fold cross validation,artificial immune system,real-world medical application,artificial immune systems,classification problem,fast fourier transform,cross validation | Data mining,Artificial immune system,Pattern recognition,Computer science,Carotid arteries,Fast Fourier transform,Artificial intelligence,Doppler effect,Cross-validation | Journal |
Volume | Issue | ISSN |
33 | 3 | Expert Systems With Applications |
Citations | PageRank | References |
11 | 0.66 | 7 |
Authors | ||
4 |
Name | Order | Citations | PageRank |
---|---|---|---|
Fatma Latifoğlu | 1 | 67 | 7.16 |
Seral Şahan | 2 | 210 | 17.86 |
Sadik Kara | 3 | 275 | 27.39 |
Salih Güneş | 4 | 1267 | 78.53 |