Smart access development for classifying lung disease with chest x-ray images using deep learning. (2021)

• Record Type: Journal Article
• Authors: kumaraguru, Tarunika; Abirami, P.; Darshan, K.M.; Angeline Kirubha, S.P.; Latha, S.; Muthu, P.
• Is Part Of: Materials today. Volume 47:Part 1(2021)
• Page Start: 76
• Page End: 79
• Publication Date: 2021
• Subjects: Covid-19 -- Pneumonia -- Deep learning -- TensorFlow -- Keras -- Django framework; Materials science -- Congresses -- Periodicals; 620.1
• DOI: 10.1016/j.matpr.2021.03.650
• Languages: English
• ISSNs: 2214-7853

Abstract

Abstract: Recently the world has come across a pandemic disease known as covid-19. The presence of symptoms of covid-19 and pneumonia may be alike to other types of lung illnesses. So, because of this, it is difficult for the affected person or medical experts to identify the condition. Chest x-ray provides general orientation which can be an initial investigative study in the analysis of lung diseases. Information from retenogram studies help the finding of covid-19 and pneumonia affecting the lungs. We use a Convolution Neural Network (CNN) in Tensor Flow and Keras based covid-19, pneumonia classification. The best fit model of CNN is then deployed in the Django framework for providing a better user interface and predicting the output.