Deep Learning Based Intelligent Classification Of Covid-19 & Pneumonia Using Cough Auscultations

The World Health Organization has designated COVID-19 a pandemic because its emergence has influenced more than 50 million world's population. Around 14 million deaths have been reported worldwide from COVID-19. In this research work, we have presented a method for autonomous screening of COVID...

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Bibliographic Details
Published in2021 6th International Multi-Topic ICT Conference (IMTIC) pp. 1 - 6
Main Authors Naqvi, Syed Zohaib Hassan, Khan, Misha Urooj, Raza, Ali, Saeed, Zubair, Abbasi, Zeeshan, Ali, Syeda Zuriat-e-Zehra
Format Conference Proceeding
LanguageEnglish
Published IEEE 10.11.2021
Subjects
Analytical models
Cough auscultation
COVID-19
Deep learning
Lung
MobileNet v2
Pandemics
Pneumonia
Pulmonary diseases
Sociology
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Summary:The World Health Organization has designated COVID-19 a pandemic because its emergence has influenced more than 50 million world's population. Around 14 million deaths have been reported worldwide from COVID-19. In this research work, we have presented a method for autonomous screening of COVID-19 and Pneumonia subjects from cough auscultation analysis. Deep learning-based model (MobileNet v2) is used to analyze a 6757 self-collected cough dataset. The experimentation has demonstrated the efficiency of the proposed technique in distinguishing between COVID-19 and Pneumonia. The results have demonstrated the cumulative accuracy of 99.98%, learning rate of 0.0005 and validation loss of 0.0028. Furthermore, cough analysis can be performed for other patients screening of other pulmonary abnormalities.
DOI:10.1109/IMTIC53841.2021.9719740