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Improving postprandial glucose forecasting using diagnosis-aware stacked learning.

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Title: Improving postprandial glucose forecasting using diagnosis-aware stacked learning.
Authors: Indriani, Fatma1, f.indriani@ulm.ac.id, Faisal, Mohammad Reza1, Said, Naufal1
Source: Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics & Control; May2026, Vol. 11 Issue 2, p349-362, 14p
Database: Applied Science & Technology Source
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Header DbId: aci
DbLabel: Applied Science & Technology Source
An: 194483274
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=aci&AN=194483274
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.22219/kinetik.v11i2.2566
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 14
        StartPage: 349
    Titles:
      – TitleFull: Improving postprandial glucose forecasting using diagnosis-aware stacked learning.
        Type: main
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          Name:
            NameFull: Indriani, Fatma
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            NameFull: Faisal, Mohammad Reza
      – PersonEntity:
          Name:
            NameFull: Said, Naufal
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          Dates:
            – D: 01
              M: 05
              Text: May2026
              Type: published
              Y: 2026
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              Value: 11
            – Type: issue
              Value: 2
          Titles:
            – TitleFull: Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics & Control
              Type: main
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