View in EDS

Using Generative Artificial Intelligence to Identify Central Line-associated Bloodstream Infections.

Saved in:
Bibliographic Details
Title: Using Generative Artificial Intelligence to Identify Central Line-associated Bloodstream Infections.
Authors: Morgan DJ; Medical Care Center, VA Maryland Healthcare System, Veterans Health Administration, U.S. Department of Veterans Affairs, Baltimore, Maryland, USA.; Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, Maryland, USA., AlShanqeeti S; Medical Care Center, VA Maryland Healthcare System, Veterans Health Administration, U.S. Department of Veterans Affairs, Baltimore, Maryland, USA.; Division of Infectious Disease, University of Maryland School of Medicine, Baltimore, Maryland, USA., Coffey KC; Medical Care Center, VA Maryland Healthcare System, Veterans Health Administration, U.S. Department of Veterans Affairs, Baltimore, Maryland, USA.; Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, Maryland, USA., Baghdadi JD; Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, Maryland, USA.; Institute for Healthcare Computing, University of Maryland, North Bethesda, Maryland, USA., Goodman KE; Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, Maryland, USA.; Institute for Healthcare Computing, University of Maryland, North Bethesda, Maryland, USA., Holman JL; VA Puget Sound Healthcare System, Veterans Health Administration, U.S. Department of Veterans Affairs, Seattle, Washington, USA.; VA National Artificial Intelligence Institute, Digital Health Office, Washington, District of Columbia, USA., Pineles L; Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, Maryland, USA.; Institute for Healthcare Computing, University of Maryland, North Bethesda, Maryland, USA., Goedken CC; VA National Artificial Intelligence Institute, Digital Health Office, Washington, District of Columbia, USA.; VA Iowa City Health Care, Veterans Health Administration, U.S. Department of Veterans Affairs, Iowa City, Iowa, USA., Firestone C; VA National Artificial Intelligence Institute, Digital Health Office, Washington, District of Columbia, USA., Branch-Elliman W; VA National Artificial Intelligence Institute, Digital Health Office, Washington, District of Columbia, USA.; VA Greater Los Angeles HCxS-West LA, Veterans Health Administration, U.S. Department of Veterans Affairs, Los Angeles, California, USA.; Department of Medicine, UCLA David Geffen School of Medicine, Los Angeles, California, USA.
Corporate Authors: VA AI CLABSI Study Group
Source: Clinical infectious diseases : an official publication of the Infectious Diseases Society of America [Clin Infect Dis] 2026 Apr 30; Vol. 82 (4), pp. e773-e780.
Publication Type: Journal Article
Journal Info: Publisher: Oxford University Press Country of Publication: United States NLM ID: 9203213 Publication Model: Print Cited Medium: Internet ISSN: 1537-6591 (Electronic) Linking ISSN: 10584838 NLM ISO Abbreviation: Clin Infect Dis Subsets: MEDLINE
Database: MEDLINE Ultimate
FullText Text:
  Availability: 0
Header DbId: mdl
DbLabel: MEDLINE Ultimate
An: 41253177
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Using Generative Artificial Intelligence to Identify Central Line-associated Bloodstream Infections.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AU" term="%22Morgan+DJ%22">Morgan DJ</searchLink>; Medical Care Center, VA Maryland Healthcare System, Veterans Health Administration, U.S. Department of Veterans Affairs, Baltimore, Maryland, USA.; Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, Maryland, USA.<br /><searchLink fieldCode="AU" term="%22AlShanqeeti+S%22">AlShanqeeti S</searchLink>; Medical Care Center, VA Maryland Healthcare System, Veterans Health Administration, U.S. Department of Veterans Affairs, Baltimore, Maryland, USA.; Division of Infectious Disease, University of Maryland School of Medicine, Baltimore, Maryland, USA.<br /><searchLink fieldCode="AU" term="%22Coffey+KC%22">Coffey KC</searchLink>; Medical Care Center, VA Maryland Healthcare System, Veterans Health Administration, U.S. Department of Veterans Affairs, Baltimore, Maryland, USA.; Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, Maryland, USA.<br /><searchLink fieldCode="AU" term="%22Baghdadi+JD%22">Baghdadi JD</searchLink>; Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, Maryland, USA.; Institute for Healthcare Computing, University of Maryland, North Bethesda, Maryland, USA.<br /><searchLink fieldCode="AU" term="%22Goodman+KE%22">Goodman KE</searchLink>; Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, Maryland, USA.; Institute for Healthcare Computing, University of Maryland, North Bethesda, Maryland, USA.<br /><searchLink fieldCode="AU" term="%22Holman+JL%22">Holman JL</searchLink>; VA Puget Sound Healthcare System, Veterans Health Administration, U.S. Department of Veterans Affairs, Seattle, Washington, USA.; VA National Artificial Intelligence Institute, Digital Health Office, Washington, District of Columbia, USA.<br /><searchLink fieldCode="AU" term="%22Pineles+L%22">Pineles L</searchLink>; Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, Maryland, USA.; Institute for Healthcare Computing, University of Maryland, North Bethesda, Maryland, USA.<br /><searchLink fieldCode="AU" term="%22Goedken+CC%22">Goedken CC</searchLink>; VA National Artificial Intelligence Institute, Digital Health Office, Washington, District of Columbia, USA.; VA Iowa City Health Care, Veterans Health Administration, U.S. Department of Veterans Affairs, Iowa City, Iowa, USA.<br /><searchLink fieldCode="AU" term="%22Firestone+C%22">Firestone C</searchLink>; VA National Artificial Intelligence Institute, Digital Health Office, Washington, District of Columbia, USA.<br /><searchLink fieldCode="AU" term="%22Branch-Elliman+W%22">Branch-Elliman W</searchLink>; VA National Artificial Intelligence Institute, Digital Health Office, Washington, District of Columbia, USA.; VA Greater Los Angeles HCxS-West LA, Veterans Health Administration, U.S. Department of Veterans Affairs, Los Angeles, California, USA.; Department of Medicine, UCLA David Geffen School of Medicine, Los Angeles, California, USA.
– Name: AuthorCorporate
  Label: Corporate Authors
  Group: Au
  Data: <searchLink fieldCode="CA" term="%22VA+AI+CLABSI+Study+Group%22">VA AI CLABSI Study Group</searchLink>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%229203213%22">Clinical infectious diseases : an official publication of the Infectious Diseases Society of America</searchLink> [Clin Infect Dis] 2026 Apr 30; Vol. 82 (4), pp. e773-e780.
– Name: TypePub
  Label: Publication Type
  Group: TypPub
  Data: Journal Article
– Name: TitleSource
  Label: Journal Info
  Group: Src
  Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22Oxford+University+Press%22">Oxford University Press </searchLink><i>Country of Publication: </i>United States <i>NLM ID: </i>9203213 <i>Publication Model: </i>Print <i>Cited Medium: </i>Internet <i>ISSN: </i>1537-6591 (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2210584838%22">10584838 </searchLink><i>NLM ISO Abbreviation: </i>Clin Infect Dis <i>Subsets: </i>MEDLINE
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=mdl&AN=41253177
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1093/cid/ciaf636
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        StartPage: e773
    Titles:
      – TitleFull: Using Generative Artificial Intelligence to Identify Central Line-associated Bloodstream Infections.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Morgan DJ
      – PersonEntity:
          Name:
            NameFull: AlShanqeeti S
      – PersonEntity:
          Name:
            NameFull: Coffey KC
      – PersonEntity:
          Name:
            NameFull: Baghdadi JD
      – PersonEntity:
          Name:
            NameFull: Goodman KE
      – PersonEntity:
          Name:
            NameFull: Holman JL
      – PersonEntity:
          Name:
            NameFull: Pineles L
      – PersonEntity:
          Name:
            NameFull: Goedken CC
      – PersonEntity:
          Name:
            NameFull: Firestone C
      – PersonEntity:
          Name:
            NameFull: Branch-Elliman W
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 30
              M: 04
              Text: 2026 Apr 30
              Type: published
              Y: 2026
          Identifiers:
            – Type: issn-electronic
              Value: 1537-6591
          Numbering:
            – Type: volume
              Value: 82
            – Type: issue
              Value: 4
          Titles:
            – TitleFull: Clinical infectious diseases : an official publication of the Infectious Diseases Society of America
              Type: main
ResultId 1