Yenidoğan kuzularda bilgisayar destekli tanı
Yükleniyor...
Dosyalar
Tarih
2020
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Pamukkale Univ
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
In our country, the number of small ruminant animals is decreasing day by day due to various reasons. In parallel with the decrease in the number of small ruminants, significant decreases are seen in animal production. One way to prevent the reduction in the number of small ruminants is to be able to make successful predictions and analysis related to the diagnosis. Thanks to computer-aided diagnostic studies performed with machine learning, the quality of health services increases while the costs of the health sector decrease. The aim of this study is to perform computer aided diagnosis in neonatal lambs using machine learning methods. Hence in study, decision tree, naive bayes, k-nearest neighbors, artificial neural networks and random forest methods were used. The performances of these classification methods were analyzed with accuracy, balanced accuracy, specifity, recall, F-measure, kappa and area under the ROC curve (AUC) criteria. As a result of the study, the Naive bayes method more successful results than other methods for computer aided diagnosis produced. It is very important that, the Naive bayes method is simple and easy to apply, achieves more successful results than other complex methods.
Açıklama
Anahtar Kelimeler
Computer-aided diagnosis, Classification, Naive bayes, Small ruminant animal
Kaynak
Pamukkale University Journal of Engineering Sciences-Pamukkale Universitesi Muhendislik Bilimleri Dergisi
WoS Q Değeri
N/A
Scopus Q Değeri
Cilt
26
Sayı
2
