Cough Audio Analysis for COVID-19 Diagnosis.

Autor: Kapoor T; Department of Computer Science and Engineering, Jaypee Institute of Information Technology, Sector-62, Noida, Uttar Pradesh 201309 India., Pandhi T; Department of Computer Science and Engineering, Jaypee Institute of Information Technology, Sector-62, Noida, Uttar Pradesh 201309 India., Gupta B; Faculty of Computer Science and Engineering, Jaypee Institute of Information Technology, Sector-62, Noida, Uttar Pradesh 201309 India.
Jazyk: angličtina
Zdroj: SN computer science [SN Comput Sci] 2023; Vol. 4 (2), pp. 125. Date of Electronic Publication: 2022 Dec 26.
DOI: 10.1007/s42979-022-01522-1
Abstrakt: Humanity has suffered catastrophically due to the COVID-19 pandemic. One of the most reliable diagnoses of COVID-19 is RT-PCR (reverse-transcription polymer chain reaction) testing. This method, however, has its limitations. It is time consuming and requires scalability. This research work carries out a preliminary prognosis of COVID-19, which is scalable and less time consuming. The research carried out a competitive analysis of four machine-learning models namely, Multilayer Perceptron, Convolutional Neural Networks, Recurrent Neural Networks with Long Short-Term Memory, and VGG-19 with Support Vector Machines. Out of these models, Multilayer Perceptron outperformed with higher specificity of 94.5% and accuracy of 96.8%. The results show that Multilayer Perceptron was able to distinguish between positive and negative COVID-19 coughs by a robust feature embedding technique.
Competing Interests: Conflict of interestOn behalf of all authors, the corresponding author states that there is no conflict of interest.
(© The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.)
Databáze: MEDLINE
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