Y Covid-19 Classification Using Deep Learning in Chest X-Ray Images

被引:0
作者
Karhan, Zehra [1 ]
Akal, Fuat [2 ]
机构
[1] Necmettin Erbakan Univ, Konya, Turkey
[2] Hacettepe Univ, Ankara, Turkey
来源
2020 MEDICAL TECHNOLOGIES CONGRESS (TIPTEKNO) | 2020年
关键词
Chest X-Ray Images; Coronavirus; Cuvid-19; Deep Learning; Transfer Learning;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Covid-19 virus, which has emerged in the Republic of China in an undetermined cause, has affected the whole world quickly. It is important to detect positive cases early to prevent further spread of the outbreak. In the diagnostic phase, radiological images of the chest are determinative as well as the RT-PCR (Reverse Transcription-Polymerase Chain Reaction) test. It was classified with the ResNet50 model, which is a convolutional neural network architecture in Covid-19 detection using chest x-ray images. Chest X-Ray image analysis can be done and infected individuals can be identified thanks to artificial intelligence quickly. The experimental results are encouraging in terms of the use of computer-aided in the field of pathology. It can also be used in situations where the possibilities and RT-PCR tests are insufficient.
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