Pneumonia Detection Using Deep Learning Methods

Faiza Mehboob Qaimkhani¹, MdGulzar Hussain¹, Ye Shiren¹ and Jiang Xingfang^2*

Abstract

A child dies of pneumonia every 39 seconds, around children dies in a year according to UNICEF, pneumonia is respiratory infection which affects the lungs, causes problem in breathing, pneumonia is detected by chest X-ray commonly, but chest X-ray of other diseases could be similar to pneumonia like lung cancer, infection etc. In order to tackle this issue, many deep learning techniques are being used in medical imaging for identifying the disease at early stages. CNN is widely using for identification and classification of diseases.In addition, features learned by pre-trained CNN models on large-scale datasets are much useful in image classification tasks, the functionality of pre-trained CNN models utilized as feature-extractors followed by different classifiers for the classification of abnormal and normal chest X-Rays. In 2019 December covid-19 diagnosed and spread whole over the world covid-19 pandemic disturbed whole world, CNN widely used for covid-19 detection using chest X-ray images datasets. In our research various deep learning models, ANN, CNN, VGG19 to detect pneumonia, and got results 94.44, 96.68, 98.27 accordingly.

Keywords

pneumonia; children; deep learning models; ANN; CNN; VGG19

Cite This Article

Qaimkhani, F. M., Hussain, M., Shiren, Y., Xingfang, J. (2022). Pneumonia Detection Using Deep Learning Methods. International Journal of Scientific Advances (IJSCIA), Volume 3| Issue 3: May-Jun 2022, Pages 489-493, URL: https://www.ijscia.com/wp-content/uploads/2022/07/Volume3-Issue3-May-Jun-No.290-489-493.pdf

Volume 3 | Issue 3: May-Jun 2022