Name
Title | ||
|---|---|---|
Medical diagnosis of rheumatoid arthritis disease from right and left hand Ulnar artery Doppler signals using adaptive network based fuzzy inference system (ANFIS) and MUSIC method |
Abstract | ||
|---|---|---|
Rheumatoid arthritis (RA) is a multi-systemic autoimmune disease that leads to substantial morbidity and mortality. In this paper, as spectral analysis methods of Multiple Signal Classification (MUSIC) method is used in order to extract the significant features from the right and left hand Ulnar artery Doppler signals for the diagnosis of RA disease. The MUSIC method has been used as subspace method. To extract features from Doppler signals obtained from the right and left hand Ulnar arterial the MUSIC method model degrees of 5, 10, 15, 20, and 25 were used. Then, an adaptive network based fuzzy inference system (ANFIS) was applied to features extracted from the right and left hand Ulnar artery Doppler signals for classifying RA disease. The methods are not new, but the study has a novelty in that the application area of these methods is new. In the hybrid model, the combination of MUSIC and ANFIS yielded classification accuracies of 95% (for a model degree of 20) using the right hand Ulnar artery and classification accuracies of 91.25% (for a model degree of 10) using left hand Ulnar artery Doppler signals in the diagnosis of RA disease. The proposed approach has potential to help with the early diagnosis of RA disease for the specialists who study this subject. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1016/j.advengsoft.2010.10.001 | Advances in Engineering Software |
Keywords | Field | DocType |
model degree,left hand,left hand ulnar artery,music method,classification accuracy,classifying ra disease,multi-systemic autoimmune disease,adaptive network based fuzzy inference system (anfis),medical diagnosis,doppler ultrasound,rheumatoid arthritis disease,hand ulnar artery doppler,right hand ulnar artery,fuzzy inference system,ra disease,adaptive network,doppler signal,ulnar artery,feature extraction | Disease,Multiple signal classification,Pattern recognition,Computer science,Theoretical computer science,Ulnar artery,Rheumatoid arthritis,Artificial intelligence,Adaptive neuro fuzzy inference system,Doppler effect,Medical diagnosis,Fuzzy inference system | Journal |
Volume | Issue | ISSN |
41 | 12 | Advances in Engineering Software |
Citations | PageRank | References |
5 | 0.46 | 15 |
Authors | ||
8 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ali Osman Özkan | 1 | 5 | 0.46 |
| Sadik Kara | 2 | 275 | 27.39 |
| Ali Salli | 3 | 5 | 0.46 |
| Mehmet Emin Sakarya | 4 | 5 | 0.79 |
| Salih Güneş | 5 | 1267 | 78.53 |
| ÖzkanAli Osman | 6 | 5 | 0.46 |
| KaraSadık | 7 | 36 | 3.47 |
| SakaryaMehmet Emin | 8 | 5 | 0.46 |