Classification of Patients with Dementia and Parkinson’s with Support Vector Machine
Yazarlar (2)
Arş. Gör. Emrah GÜRLEK Kırşehir Ahi Evran Üniversitesi, Türkiye
Dr. Öğr. Üyesi İnci Zaim Gökbay Istanbul Üniversitesi, Türkiye
| Bildiri Türü | Tebliğ/Bildiri | Bildiri Dili | İngilizce |
| Bildiri Alt Türü | Tam Metin Olarak Yayınlanan Tebliğ (Uluslararası Kongre/Sempozyum) | ||
| Bildiri Niteliği | Alanında Hakemli Uluslararası Kongre/Sempozyum | ||
| DOI Numarası | 10.1109/ASYU58738.2023.10296584 | ||
| Kongre Adı | 2023 Innovations in Intelligent Systems and Applications Conference (ASYU) | ||
| Kongre Tarihi | 11-10-2023 / 13-10-2023 | ||
| Basıldığı Ülke | Türkiye | Basıldığı Şehir | Sivas |
| Bildiri Linki | https://ieeexplore.ieee.org/document/10296584/keywords#keywords | ||
| UAK Araştırma Alanları |
Ziraat, Orman ve Su Ürünleri
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| Özet |
| Clinical findings and magnetic resonance images are used to diagnose dementia and Parkinson’s, which are neurodegenerative diseases. Studies are carried out for prediction of neurodegenerative diseases and/or for the efficient treatment process. Although there are studies that address and classify neurodegenerative diseases such as dementia and Parkinson’s individually with healthy control groups to accelerate the diagnosis stage, there are no studies that include two or more diseases at the same time. We aimed to make an original contribution to the literature by considering dementia and Parkinson’s diseases together. In our study, where we classify dementia and Parkinson’s on the differences in brain volume and brain thickness, we used the voxel-based morphometry technique for the volumetric measurement of shrinkage and the support vector machine (SVM) algorithm for the estimation of the … |
| Anahtar Kelimeler |
| dementia | Parkinson's Disease | support vector machine | voxel-based morphometry |
BM Sürdürülebilir Kalkınma Amaçları
| Atıf Sayıları | |
| Scopus | 1 |
| Google Scholar | 1 |