Pneumonia Detection Using Deep Learning Methods
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A child dies of pneumonia every 39 seconds, around children, die in a year according to UNICEF, pneumonia is a respiratory infection that affects the lungs and causes problems breathing, pneumonia is detected by chest Xray commonly, but chest X-rays 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 its early stages. CNN is widely used for the 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 was diagnosed and spread whole over the world covid-19 pandemic disturbed the whole world, and CNN was widely used for covid-19 detection using chest X-ray images datasets. In our research various deep learning models, ANN, CNN, and VGG19 to detect pneumonia and got results of 94.44, 96.68, and 98.27 accordingly.
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