View in EDS HTML Full Text PDF Full Text

Predicting the future risk and outcomes of severe heart failure and coronary artery disease with machine learning in the UK Biobank Cohort.

Saved in:
Bibliographic Details
Title: Predicting the future risk and outcomes of severe heart failure and coronary artery disease with machine learning in the UK Biobank Cohort.
Authors: Taha, Karim1 (AUTHOR), Ross, Heather J.1 (AUTHOR), Peikari, Mohammad1 (AUTHOR), Mueller, Brigitte1 (AUTHOR), Fan, Chun-Po S.1 (AUTHOR), Crowdy, Edgar1 (AUTHOR), Moayedi, Yas1 (AUTHOR), Billia, Filio1 (AUTHOR), Manlhiot, Cedric1,2 (AUTHOR) cmanlhi1@jhmi.edu
Source: PLoS ONE. 9/10/2025, Vol. 20 Issue 9, p1-16. 16p.
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: 187861938
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Predicting the future risk and outcomes of severe heart failure and coronary artery disease with machine learning in the UK Biobank Cohort.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Taha%2C+Karim%22">Taha, Karim</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Ross%2C+Heather+J%2E%22">Ross, Heather J.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Peikari%2C+Mohammad%22">Peikari, Mohammad</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Mueller%2C+Brigitte%22">Mueller, Brigitte</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Fan%2C+Chun-Po+S%2E%22">Fan, Chun-Po S.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Crowdy%2C+Edgar%22">Crowdy, Edgar</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Moayedi%2C+Yas%22">Moayedi, Yas</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Billia%2C+Filio%22">Billia, Filio</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Manlhiot%2C+Cedric%22">Manlhiot, Cedric</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<i> cmanlhi1@jhmi.edu</i>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22PLoS+ONE%22">PLoS ONE</searchLink>. 9/10/2025, Vol. 20 Issue 9, p1-16. 16p.
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=asn&AN=187861938
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1371/journal.pone.0329461
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 16
        StartPage: 1
    Titles:
      – TitleFull: Predicting the future risk and outcomes of severe heart failure and coronary artery disease with machine learning in the UK Biobank Cohort.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Taha, Karim
      – PersonEntity:
          Name:
            NameFull: Ross, Heather J.
      – PersonEntity:
          Name:
            NameFull: Peikari, Mohammad
      – PersonEntity:
          Name:
            NameFull: Mueller, Brigitte
      – PersonEntity:
          Name:
            NameFull: Fan, Chun-Po S.
      – PersonEntity:
          Name:
            NameFull: Crowdy, Edgar
      – PersonEntity:
          Name:
            NameFull: Moayedi, Yas
      – PersonEntity:
          Name:
            NameFull: Billia, Filio
      – PersonEntity:
          Name:
            NameFull: Manlhiot, Cedric
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 10
              M: 09
              Text: 9/10/2025
              Type: published
              Y: 2025
          Identifiers:
            – Type: issn-print
              Value: 19326203
          Numbering:
            – Type: volume
              Value: 20
            – Type: issue
              Value: 9
          Titles:
            – TitleFull: PLoS ONE
              Type: main
ResultId 1