Artificial Intelligence in UK Hospital Medicine: From Innovation to Implementation.
Artificial Intelligence (AI) has the potential to enhance patient care in the UK's increasingly pressured healthcare system. As AI's applications in healthcare are expanding, healthcare professionals should understand the processes underpinning how AI tools translate from research to clinical applic...
| Publicado en: | British Journal of Hospital Medicine (17508460) Vol. 86; no. 12; pp. 1 - 27 |
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| Autores principales: | , , , |
| Formato: | pictorial review tables/charts Journal Article |
| Publicado: |
Mark Allen Holdings Limited
Dec2025
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| 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=190495307&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 190495307 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 17508460 25KN jtl: British Journal of Hospital Medicine (17508460) issn: 17508460 maglogo: N pubinfo: dt: Dec2025 vid: 86 iid: 12 pid: 11383 pub: Mark Allen Holdings Limited artinfo: ui: 190495307 190495307 192915040 190495307 10.12968/hmed.2025.0468 190495307 ppf: 1 ppct: 26 formats: tig: atl: Artificial Intelligence in UK Hospital Medicine: From Innovation to Implementation. aug: au: Carroll, Dervla Boodhoo, Vijna Lowe, David J Carlin, Christopher affil: Digital Health Validation Lab, College of Medicine, Veterinary and Life Sciences, University of Glasgow, Glasgow, UK sug: subj: Artificial Intelligence Utilization Hospital Medicine United Kingdom Diffusion of Innovation Implementation Science Health Care Delivery United Kingdom Routinely Collected Health Data Equipment and Supplies Legislation and Jurisprudence Health Expenditures Patient Safety Patient Care National Health Programs Scotland Northern Ireland England Wales ab: Artificial Intelligence (AI) has the potential to enhance patient care in the UK's increasingly pressured healthcare system. As AI's applications in healthcare are expanding, healthcare professionals should understand the processes underpinning how AI tools translate from research to clinical application. There are several stages: (1) training and validation on healthcare data, (2) generation of evidence demonstrating performance and safety, (3) regulatory compliance, (4) AI product procurement, (5) implementation in clinical settings, and (6) ongoing monitoring and oversight of deployed AI. Each step presents unique challenges and opportunities that can influence successful integration. Clinicians should understand AI's capabilities and limitations to ensure its appropriate and effective use in practice. This review aims to provide a structured overview of the AI adoption pathway in healthcare, with a view to supporting clinicians in critically appraising its potential and limitations, optimising its integration into clinical practice, and engaging with AI in an informed manner. pubtype: Academic Journal doctype: pictorial review tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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