View in EDS HTML Full Text PDF Full Text

OSCAR: Optimal subset cardinality regression using the L0-pseudonorm with applications to prognostic modelling of prostate cancer.

Saved in:
Bibliographic Details
Title: OSCAR: Optimal subset cardinality regression using the L0-pseudonorm with applications to prognostic modelling of prostate cancer.
Authors: Halkola, Anni S.1 (AUTHOR), Joki, Kaisa1 (AUTHOR), Mirtti, Tuomas2,3,4 (AUTHOR), Mäkelä, Marko M.1 (AUTHOR), Aittokallio, Tero1,5,6,7 (AUTHOR), Laajala, Teemu D.1,8 (AUTHOR) teelaa@utu.fi
Source: PLoS Computational Biology. 3/10/2023, Vol. 19 Issue 3, p1-30. 30p. 2 Diagrams, 2 Charts, 7 Graphs.
Database: Academic Search Ultimate
Full text is not displayed to guests.
FullText Links:
  – Type: pdflink
Text:
  Availability: 1
Header DbId: asn
DbLabel: Academic Search Ultimate
An: 162353076
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: OSCAR: Optimal subset cardinality regression using the L0-pseudonorm with applications to prognostic modelling of prostate cancer.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Halkola%2C+Anni+S%2E%22">Halkola, Anni S.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Joki%2C+Kaisa%22">Joki, Kaisa</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Mirtti%2C+Tuomas%22">Mirtti, Tuomas</searchLink><relatesTo>2,3,4</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Mäkelä%2C+Marko+M%2E%22">Mäkelä, Marko M.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Aittokallio%2C+Tero%22">Aittokallio, Tero</searchLink><relatesTo>1,5,6,7</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Laajala%2C+Teemu+D%2E%22">Laajala, Teemu D.</searchLink><relatesTo>1,8</relatesTo> (AUTHOR)<i> teelaa@utu.fi</i>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22PLoS+Computational+Biology%22">PLoS Computational Biology</searchLink>. 3/10/2023, Vol. 19 Issue 3, p1-30. 30p. 2 Diagrams, 2 Charts, 7 Graphs.
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=asn&AN=162353076
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1371/journal.pcbi.1010333
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 30
        StartPage: 1
    Titles:
      – TitleFull: OSCAR: Optimal subset cardinality regression using the L0-pseudonorm with applications to prognostic modelling of prostate cancer.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Halkola, Anni S.
      – PersonEntity:
          Name:
            NameFull: Joki, Kaisa
      – PersonEntity:
          Name:
            NameFull: Mirtti, Tuomas
      – PersonEntity:
          Name:
            NameFull: Mäkelä, Marko M.
      – PersonEntity:
          Name:
            NameFull: Aittokallio, Tero
      – PersonEntity:
          Name:
            NameFull: Laajala, Teemu D.
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 10
              M: 03
              Text: 3/10/2023
              Type: published
              Y: 2023
          Identifiers:
            – Type: issn-print
              Value: 1553734X
          Numbering:
            – Type: volume
              Value: 19
            – Type: issue
              Value: 3
          Titles:
            – TitleFull: PLoS Computational Biology
              Type: main
ResultId 1