Alt Uzay k-NN ile Eritmato-Skuamöz Hastalık Türlerinin Sınıflandırılması
Öz
Anahtar Kelimeler
Kaynakça
- [1] Güvenir H. A. ve Emeksiz N., "An expert system for the differential diagnosis of erythemato-squamous diseases," Expert Systems with Applications, 2000; 18: 43-49.
- [2] Güvenir, H. A., Demiröz, G. ve İlter, N. "Learning differential diagnosis of erythemato-squamous diseases using voting feature intervals," Artificial Intelligence in Medicine, 1998; 13: 147-165.
- [3] Elsayad, A., Dhaifullah, M., Nassef A. M., Analysis and Diagnosis of Erythemato-Squamous Diseases Using CHAID Decision Trees,15th International Multi-Conference on Systems, Signals & Devices (SSD), 2018.
- [4] Maghooli, K., Langarizadeh, M., Shahmoradi. L, Habibikoolaee, M., Jebraeily, M. and Bouraghi, H., Differential Diagnosis of Erythmato Squamous Diseases Using Classification and Regression Tree, Acta Inform Med. 2016 OCT; 24(5): 338-34.
- [5] Wang, L. and Sui, T. Z. "Application of Data Mining Technology Based on Neural Network in the Engineering," in International Conference on Wireless Communications, Networking and Mobile Computing, 2007, pp. 5544-5547.
- [6] Baumgartner, C., Knowledge Discovery and Data Mining in Biomedicine, Thesis for Habilitation, University for Health Sciences, Medical Informatics and Technology, 2005.
- [7] Bache, K. and Lichman, M.,“{UCI} Machine Learning Repository”, University of California, Irvine, School of Information and Computer Sciences, 2013.
- [8] http://archive.ics.uci.edu/ml/datasets/Dermatology.
Ayrıntılar
Birincil Dil
Türkçe
Konular
Mühendislik
Bölüm
Araştırma Makalesi
Yazarlar
Duygu Kaya
*
0000-0002-6453-631X
Türkiye
Yayımlanma Tarihi
27 Eylül 2019
Gönderilme Tarihi
4 Şubat 2019
Kabul Tarihi
10 Haziran 2019
Yayımlandığı Sayı
Yıl 2019 Cilt: 31 Sayı: 2