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In this study, a clustering algorithm based on adaptive neural fuzzy inference system (ANFIS) was used for computer-assisted diagnosis of the vertebral column disorder from machine learning databases of UCI (University of California Irvine). Features of pelvic incidence, pelvic tilt and lumbar lordosis angle given in this dataset was applied to the inputs of the algorithm. The performance of algorithm was evaluated using mean square error and regression coefficient criteria to discriminate patients with vertebral column disease from healthy subjects. As a result, the classification performance of 90.82% was obtained by using the generated model of ANFIS. © 2018 IEEE.
| Yazar |
Uzun, Rukiye İşler, Yalçın Erkaymaz, Okan Kocadayı, Yasemin |
| Yayın Türü | Proceedings |
| Tek Biçim Adres | https://hdl.handle.net/20.500.12628/4870 |
| Konu Başlıkları |
ANFIS
Clustering Diagnosis Machine learning Vertebral column |
| Koleksiyonlar |
Fakülteler Mühendislik Fakültesi Elektrik - Elektronik Mühendisliği Bölümü Bildiri Koleksiyonu (Elektrik - Elektronik Mühendisliği Bölümü) Araştırma Çıktıları | WoS | Scopus | TR-Dizin | PubMed | SOBİAD Scopus İndeksli Yayınlar Koleksiyonu |
| Dergi Adı | 26th IEEE Signal Processing and Communications Applications Conference, SIU 2018 |
| Sayfalar | 1 - 4 |
| Yayın Yılı | 2018 |
| Eser Adı [dc.title] | Computer-assisted diagnosis of vertebral column diseases by adaptive neuro-fuzzy inference system |
| Yazar [dc.contributor.author] | Uzun, Rukiye |
| Yazar [dc.contributor.author] | İşler, Yalçın |
| Yazar [dc.contributor.author] | Erkaymaz, Okan |
| Yazar [dc.contributor.author] | Kocadayı, Yasemin |
| Yayın Yılı [dc.date.issued] | 2018 |
| Yayıncı [dc.publisher] | Institute of Electrical and Electronics Engineers Inc. |
| Yayın Türü [dc.type] | proceedings |
| Açıklama [dc.description] | Aselsan;et al.;Huawei;IEEE Signal Processing Society;IEEE Turkey Section;Netas |
| Açıklama [dc.description] | 26th IEEE Signal Processing and Communications Applications Conference, SIU 2018 -- 2 May 2018 through 5 May 2018 -- -- 137780 |
| Özet [dc.description.abstract] | In this study, a clustering algorithm based on adaptive neural fuzzy inference system (ANFIS) was used for computer-assisted diagnosis of the vertebral column disorder from machine learning databases of UCI (University of California Irvine). Features of pelvic incidence, pelvic tilt and lumbar lordosis angle given in this dataset was applied to the inputs of the algorithm. The performance of algorithm was evaluated using mean square error and regression coefficient criteria to discriminate patients with vertebral column disease from healthy subjects. As a result, the classification performance of 90.82% was obtained by using the generated model of ANFIS. © 2018 IEEE. |
| Kayıt Giriş Tarihi [dc.date.accessioned] | 2019-12-23 |
| Açık Erişim Tarihi [dc.date.available] | 2019-12-23 |
| Yayın Dili [dc.language.iso] | tur |
| Konu Başlıkları [dc.subject] | ANFIS |
| Konu Başlıkları [dc.subject] | Clustering |
| Konu Başlıkları [dc.subject] | Diagnosis |
| Konu Başlıkları [dc.subject] | Machine learning |
| Konu Başlıkları [dc.subject] | Vertebral column |
| Haklar [dc.rights] | info:eu-repo/semantics/closedAccess |
| Alternatif Başlık [dc.title.alternative] | Adaptif sinirsel bulanık çıkarım sistemi ile omurga rahatsızlığının bilgisayar destekli teşhisi |
| İlk Sayfa Sayısı [dc.identifier.startpage] | 1 |
| Son Sayfa Sayısı [dc.identifier.endpage] | 4 |
| Dergi Adı [dc.relation.journal] | 26th IEEE Signal Processing and Communications Applications Conference, SIU 2018 |
| Tek Biçim Adres [dc.identifier.uri] | https://dx.doi.org/10.1109/SIU.2018.8404736 |
| Tek Biçim Adres [dc.identifier.uri] | https://hdl.handle.net/20.500.12628/4870 |