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Machine learning based detection of T–wave alternans in real ambulatory conditions.

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Title: Machine learning based detection of T–wave alternans in real ambulatory conditions.
Authors: Pascual-Sánchez, Lidia1, lidia.pascual@uah.es, Goya-Esteban, Rebeca2, rebeca.goyaesteban@urjc.es, Cruz-Roldán, Fernando1, fernando.cruz@uah.es, Hernández-Madrid, Antonio3, antonio.hernandez@uah.es, Blanco-Velasco, Manuel1, manuel.blanco@uah.es
Source: Computer Methods & Programs in Biomedicine; Jun2024, Vol. 249, pN.PAG-N.PAG, 1p
Database: Applied Science & Technology Source
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  Availability: 0
Header DbId: aci
DbLabel: Applied Science & Technology Source
An: 176648929
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
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  Data: Machine learning based detection of T–wave alternans in real ambulatory conditions.
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  Data: <searchLink fieldCode="JN" term="%22Computer+Methods+%26+Programs+in+Biomedicine%22">Computer Methods & Programs in Biomedicine</searchLink>; Jun2024, Vol. 249, pN.PAG-N.PAG, 1p
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=176648929
RecordInfo BibRecord:
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      – Type: doi
        Value: 10.1016/j.cmpb.2024.108157
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      – Code: eng
        Text: English
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        PageCount: 1
        StartPage: N.PAG
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      – TitleFull: Machine learning based detection of T–wave alternans in real ambulatory conditions.
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          Name:
            NameFull: Pascual-Sánchez, Lidia
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            NameFull: Goya-Esteban, Rebeca
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            NameFull: Cruz-Roldán, Fernando
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            NameFull: Hernández-Madrid, Antonio
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            NameFull: Blanco-Velasco, Manuel
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            – D: 01
              M: 06
              Text: Jun2024
              Type: published
              Y: 2024
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              Value: 01692607
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              Value: 249
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