Surgical scene understanding and the structural validation gap in an industry-led AI ecosystem.

Detalles Bibliográficos
Publicado en:NPJ Digital Medicine Vol. 9; no. 1; pp. 1 - 3
Autores principales: MacAonghusa, Pol, Cahill, Ronan A.
Formato: commentary tables/charts Journal Article
Publicado: Springer Nature 8/10/2026
Acceso en línea:Ver este registro en EBSCOhost
fields @attributes:
  recordID: 1
pdfLink:
plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=196062212&site=ehost-live
header:
  @attributes:
    shortDbName: ccm
    uiTerm: 196062212
    longDbName: CINAHL Complete
    uiTag: AN
  controlInfo:
    bkinfo:
    dissinfo:
    jinfo:
      jid:
        23986352
        LQV4
      jtl: NPJ Digital Medicine
      issn: 23986352
      maglogo: N
    pubinfo:
      dt: 8/10/2026
      vid: 9
      iid: 1
      pid: 237
      pub: Springer Nature
      place: New York, New York
    artinfo:
      ui:
        196062212
        196062212
        196062212
        10.1038/s41746-026-03029-y
        196062212
      ppf: 1
      ppct: 2
      formats:
      tig:
        atl: Surgical scene understanding and the structural validation gap in an industry-led AI ecosystem.
      aug:
        au:
          MacAonghusa, Pol
          Cahill, Ronan A.
        affil: https://ror.org/05m7pjf47 UCD Centre for Precision Surgery, University College Dublin, Dublin, Ireland
      sug:
        subj:
          Surgery, Laparoscopic
          Videorecording
          Data Curation
          Artificial Intelligence
          Minimally Invasive Procedures
          Workflow
          Decision Support Systems, Clinical
          Implementation Science
          Patient Safety
      pubtype: Academic Journal
      doctype:
        commentary
        tables/charts
        Journal Article
      ougenre: Unknown
      ab:
    language: English
    refInfo:
    holdings:
      @attributes:
        islocal: N