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Classification of arrhythmia electrocardiogram signals using kernel principal component analysis and naïve bayes.

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Title: Classification of arrhythmia electrocardiogram signals using kernel principal component analysis and naïve bayes.
Authors: Melinda, Melinda1, melinda@usk.ac.id, Farhan1, Irhamsyah, Muhammad1, Miftahujjannah, Rizka1, Acula, Donata D.2, Yunidar, Yunidar1
Source: Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics & Control; Aug2025, Vol. 10 Issue 3, p283-295, 13p
Database: Applied Science & Technology Source
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  Availability: 0
Header DbId: aci
DbLabel: Applied Science & Technology Source
An: 187738945
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
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  Data: Classification of arrhythmia electrocardiogram signals using kernel principal component analysis and naïve bayes.
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PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=187738945
RecordInfo BibRecord:
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      – Type: doi
        Value: 10.22219/kinetik.v10i3.2219
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      – Code: eng
        Text: English
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        PageCount: 13
        StartPage: 283
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      – TitleFull: Classification of arrhythmia electrocardiogram signals using kernel principal component analysis and naïve bayes.
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          Name:
            NameFull: Melinda, Melinda
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            NameFull: Farhan
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            NameFull: Irhamsyah, Muhammad
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            NameFull: Miftahujjannah, Rizka
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            NameFull: Acula, Donata D.
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            – D: 01
              M: 08
              Text: Aug2025
              Type: published
              Y: 2025
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            – TitleFull: Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics & Control
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