USING DEEP LEARNING TO SUPPORT DIAGNOSIS OF PNEUMONIA
WITH X-RAY IMAGES
Authors: Vo Duc Quang
Vinh University Journal of Science
: NT24 : NT24
Publishing year: 12/2021
In the context of the outbreak of the COVID-19 epidemic in Vietnam and
around the world, an artificial intelligence application that accurately diagnoses pneumonia will
help reduce time and human resources for medical examination and treatment. This helps patients
receive timely treatment, reducing the risk of aggravation and death. This paper presents the
characteristics of modern deep learning network architectures based on convolutional neural
networks such as ResNet50, VGG16, Inception, DenseNet. Thereby performing a test to evaluate
these models in the diagnosis of pneumonia using the Chest-Xray dataset. The test results show
that the deep learning model using VGG16 deep learning network architecture gives the highest
accuracy rate. This is the basis for proposing to build an application to support effective
pneumonia diagnosis based on X-ray images.
Deep learning, Covid19, VGG16, CNN, X-ray images