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

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 g...

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Detalles Bibliográficos
Autores principales: kumaraguru, Tarunika, Abirami, P., Darshan, K.M., Angeline Kirubha, S.P., Latha, S., Muthu, P.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Ltd. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8049837/
https://www.ncbi.nlm.nih.gov/pubmed/33880332
http://dx.doi.org/10.1016/j.matpr.2021.03.650
Descripción
Sumario: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.