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Survey on the perceptions of UK gastroenterologists and endoscopists to artificial intelligence.
Kader, Rawen; Baggaley, Rebecca F; Hussein, Mohamed; Ahmad, Omer F; Patel, Nisha; Corbett, Gareth; Dolwani, Sunil; Stoyanov, Danail; Lovat, Laurence B.
Afiliación
  • Kader R; Division of Surgery and Interventional Sciences, University College London, London, UK.
  • Baggaley RF; Wellcome/EPSRC Centre for Interventional and Surgical Sciences (WEISS), University College London, London, UK.
  • Hussein M; Department of Gastroenterology, University College London Hospitals NHS Foundation Trust, London, UK.
  • Ahmad OF; Department of Respiratory Infections, University of Leicester, Leicester, UK.
  • Patel N; Division of Surgery and Interventional Sciences, University College London, London, UK.
  • Corbett G; Department of Gastroenterology, University College London Hospitals NHS Foundation Trust, London, UK.
  • Dolwani S; Wellcome/EPSRC Centre for Interventional and Surgical Sciences (WEISS), University College London, London, UK.
  • Stoyanov D; Department of Gastroenterology, University College London Hospitals NHS Foundation Trust, London, UK.
  • Lovat LB; Department of Gastroenterology, Imperial College Healthcare NHS Trust, London, UK.
Frontline Gastroenterol ; 13(5): 423-429, 2022.
Article en En | MEDLINE | ID: mdl-36046492
ABSTRACT
Background and

aims:

With the potential integration of artificial intelligence (AI) into clinical practice, it is essential to understand end users' perception of this novel technology. The aim of this study, which was endorsed by the British Society of Gastroenterology (BSG), was to evaluate the UK gastroenterology and endoscopy communities' views on AI.

Methods:

An online survey was developed and disseminated to gastroenterologists and endoscopists across the UK.

Results:

One hundred four participants completed the survey. Quality improvement in endoscopy (97%) and better endoscopic diagnosis (92%) were perceived as the most beneficial applications of AI to clinical practice. The most significant challenges were accountability for incorrect diagnoses (85%) and potential bias of algorithms (82%). A lack of guidelines (92%) was identified as the greatest barrier to adopting AI in routine clinical practice. Participants identified real-time endoscopic image diagnosis (95%) as a research priority for AI, while the most perceived significant barriers to AI research were funding (82%) and the availability of annotated data (76%). Participants consider the priorities for the BSG AI Task Force to be identifying research priorities (96%), guidelines for adopting AI devices in clinical practice (93%) and supporting the delivery of multicentre clinical trials (91%).

Conclusion:

This survey has identified views from the UK gastroenterology and endoscopy community regarding AI in clinical practice and research, and identified priorities for the newly formed BSG AI Task Force.
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Texto completo: 1 Bases de datos: MEDLINE Tipo de estudio: Guideline / Qualitative_research Idioma: En Revista: Frontline Gastroenterol Año: 2022 Tipo del documento: Article País de afiliación: Reino Unido

Texto completo: 1 Bases de datos: MEDLINE Tipo de estudio: Guideline / Qualitative_research Idioma: En Revista: Frontline Gastroenterol Año: 2022 Tipo del documento: Article País de afiliación: Reino Unido