Analysis and Estimation of Pathological Data and Findings with Deep Learning Methods

Yıl 2022, Cilt: 7 Sayı: 3, 175 - 187, 31.12.2022

Ahmet Anıl Şakır Ali Hakan Işık Özlem Özmen Volkan İpek

https://doi.org/10.24880/maeuvfd.1121112

Öz

As in human diseases, rapid diagnosis of animal diseases is of great importance. In order for the disease treatments to be carried out properly, the diagnosis must be of high accuracy, as well as the rapid diagnosis. In this study, the disease types in the data set consisting of the data examined between the years 2000-2020 belonging to the Department of Pathology of the Faculty of Veterinary Medicine of Burdur Mehmet Akif Ersoy University were estimated by using the decision tree classification model and the KNN classification model. Categories such as age, type, city, and gender in the data set were analyzed in graphics. For the estimation and analysis processes to give accurate results, the data set was corrected by going through some pre-processes and the missing data in the data set was completed. It is thought that the results obtained from the estimation and analysis will allow rapid and accurate diagnosis in animal disease diagnoses.

Anahtar Kelimeler

Pathology, classification, decision tree, KNN, deep learning

Destekleyen Kurum

Burdur Mehmet Akif Ersoy Üniversitesi Bilimsel Araştırma Projeleri Koordinatörlüğü

Proje Numarası

0671-YL-20

Teşekkür

The present M.Sc. Thesis was supported by Burdur Mehmet Akif Ersoy University Scientific Research Projects Under the Project number of 0671-YL-20

Kaynakça

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