%0 Journal Article
%T Detection of Pneumonia with Deep Learning Model
%A Burhan ERGEN
%A Mehmet Emre SERTKAYA
%A Mesut TO£¿A£¿AR
%J -
%D 2019
%X Recently, rapid developments in image processing have gained different perspective in deep learning models. Deep learning models continue to contribute to the areas of human health. Pneumonia is one of the diseases that people may encounter in any period of their lives. Pneumonia accounts for about 18% of infectious diseases. In some cases, this disease can cause death. In this study, lung x-ray images were used for the diagnosis of pneumonia. The ESA from deep learning models was used for feature extraction in the resulting image set. The results of CNN with different classifiers were compared. As a result of the comparison, a success rate of approximately 95.8% was obtained with support vector machines. In the early diagnosis of deadly diseases such as pneumonia, deep learning models were found to be faster and more accurate. This study has shown that feature extraction with CNN provides better results in terms of time and performance than current methods in biomedical field
%K ESA
%K Derin £¿£¿renme
%K G£¿r¨¹nt¨¹ i£¿leme
%K Biyomedikal
%K Zat¨¹rre hastal£¿£¿£¿
%U http://dergipark.org.tr/fumbd/issue/43638/498364