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COVID-19 Prognosis from Chest X-ray Images by using Deep Learning Approaches: A Next Generation Diagnostic Tool

Medicine and Health

COVID-19 Prognosis from Chest X-ray Images by using Deep Learning Approaches: A Next Generation Diagnostic Tool

M. Pal, S. Parij, et al.

This exciting research conducted by Madhumita Pal, Smit Parij, Ganapati Pan, Snehasish Mishra, Ranjan K Mohapatra, and Kuldeep Dhama explores the powerful application of deep learning models, VGG-16 and LSTM, for accurate COVID-19 diagnosis from chest X-ray images. The findings illustrate impressive classification accuracy, making it a promising tool for swift COVID-19 screening in challenging environments.

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Playback language: English
Abstract
This study investigates the use of deep learning models, specifically VGG-16 and LSTM, to diagnose COVID-19 from chest X-ray (CXR) images. The models were trained on a dataset of CXR images from normal, pneumonia, and COVID-19 patients. The results demonstrate high accuracy in classifying these three categories, highlighting the potential of this approach for rapid and efficient COVID-19 screening, especially in resource-constrained settings.
Publisher
Journal of Pure and Applied Microbiology
Published On
May 04, 2023
Authors
Madhumita Pal, Smit Parij, Ganapati Pan, Snehasish Mishra, Ranjan K Mohapatra, Kuldeep Dhama
Tags
deep learning
COVID-19
chest X-ray
VGG-16
LSTM
diagnosis
classification

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