Detection of tuberculosis using cough audio analysis: a deep learning approach with capsule networks
- Location
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Deutsche Nationalbibliothek Frankfurt am Main
- Extent
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1 Online-Ressource.
- Language
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Englisch
- Bibliographic citation
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Detection of tuberculosis using cough audio analysis: a deep learning approach with capsule networks ; volume:4 ; number:1 ; day:4 ; month:11 ; year:2024 ; pages:1-11 ; date:12.2024
Discover artificial intelligence ; 4, Heft 1 (4.11.2024), 1-11, 12.2024
- Creator
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Rajasekar, Sakthi Jaya Sundar
Balaraman, Anu Rithiga
Balaraman, Deepa Varnika
Mohamed Ali, Saleem
Narasimhan, Kannan
Krishnasamy, Narayanasamy
Perumal, Varalakshmi
- Contributor
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SpringerLink (Online service)
- DOI
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10.1007/s44163-024-00179-4
- URN
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urn:nbn:de:101:1-2501222113338.075662730059
- Rights
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Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
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15.08.2025, 7:31 AM CEST
Data provider
This object is provided by:
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Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Associated
- Rajasekar, Sakthi Jaya Sundar
- Balaraman, Anu Rithiga
- Balaraman, Deepa Varnika
- Mohamed Ali, Saleem
- Narasimhan, Kannan
- Krishnasamy, Narayanasamy
- Perumal, Varalakshmi
- SpringerLink (Online service)
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Data reduction for cough studies using distribution of audio frequency content
Cough
The Deep Capsule Prior – advantages through complexity?
"Cough officer screening" improves detection of pulmonary tuberculosis in hospital in-patients
Detection of pulmonary tuberculosis among patients with cough attending outpatient departments in Dar Es Salaam, Tanzania: does duration of cough matter?
Field test of a novel detection device for Mycobacterium tuberculosis antigen in cough
Mycobacterium tuberculosis cough aerosol culture status associates with host characteristics and inflammatory profiles