Approach to COVID-19 time series data using deep learning and spectral analysis methods.
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| Title: | Approach to COVID-19 time series data using deep learning and spectral analysis methods. |
|---|---|
| Authors: | Oshinubi, Kayode1, Amakor, Augustina2, Peter, Olumuyiwa James3, Rachdi, Mustapha1, Demongeot, Jacques1 Jacques.Demongeot@univ-grenoble-alpes.fr |
| Source: | AIMS Bioengineering. 2022, Vol. 9 Issue 1, p1-21. 21p. |
| Database: | Academic Search Ultimate |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
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| Header | DbId: asn DbLabel: Academic Search Ultimate An: 155328272 AccessLevel: 2 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=asn&AN=155328272 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.3934/bioeng.2022001 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 21 StartPage: 1 Titles: – TitleFull: Approach to COVID-19 time series data using deep learning and spectral analysis methods. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Oshinubi, Kayode – PersonEntity: Name: NameFull: Amakor, Augustina – PersonEntity: Name: NameFull: Peter, Olumuyiwa James – PersonEntity: Name: NameFull: Rachdi, Mustapha – PersonEntity: Name: NameFull: Demongeot, Jacques IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 01 Text: 2022 Type: published Y: 2022 Identifiers: – Type: issn-print Value: 23751495 Numbering: – Type: volume Value: 9 – Type: issue Value: 1 Titles: – TitleFull: AIMS Bioengineering Type: main |
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