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Attitudes of the Surgical Team Toward Artificial Intelligence in Neurosurgery: International 2-Stage Cross-Sectional Survey.
Layard Horsfall, Hugo; Palmisciano, Paolo; Khan, Danyal Z; Muirhead, William; Koh, Chan Hee; Stoyanov, Danail; Marcus, Hani J.
  • Layard Horsfall H; Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, University College, London, United Kingdom; Wellcome EPSRC Centre for Interventional and Surgical Sciences, University College, London, United Kingdom. Electronic address: Hugo.layardhorsfall@ucl.ac.uk.
  • Palmisciano P; Department of Neurosurgery, Policlinico Gaspare Rodolico, Catania, Italy.
  • Khan DZ; Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, University College, London, United Kingdom; Wellcome EPSRC Centre for Interventional and Surgical Sciences, University College, London, United Kingdom.
  • Muirhead W; Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, University College, London, United Kingdom; Wellcome EPSRC Centre for Interventional and Surgical Sciences, University College, London, United Kingdom.
  • Koh CH; Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, University College, London, United Kingdom; Wellcome EPSRC Centre for Interventional and Surgical Sciences, University College, London, United Kingdom.
  • Stoyanov D; Wellcome EPSRC Centre for Interventional and Surgical Sciences, University College, London, United Kingdom.
  • Marcus HJ; Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, University College, London, United Kingdom; Wellcome EPSRC Centre for Interventional and Surgical Sciences, University College, London, United Kingdom.
World Neurosurg ; 146: e724-e730, 2021 02.
Article en En | MEDLINE | ID: mdl-33248306
BACKGROUND: Artificial intelligence (AI) has the potential to disrupt how we diagnose and treat patients. Previous work by our group has demonstrated that the majority of patients and their relatives feel comfortable with the application of AI to augment surgical care. The aim of this study was to similarly evaluate the attitudes of surgeons and the wider surgical team toward the role of AI in neurosurgery. METHODS: In a 2-stage cross sectional survey, an initial open-question qualitative survey was created to determine the perspective of the surgical team on AI in neurosurgery including surgeons, anesthetists, nurses, and operating room practitioners. Thematic analysis was performed to develop a second-stage quantitative survey that was distributed via social media. We assessed the extent to which they agreed and were comfortable with real-world AI implementation using a 5-point Likert scale. RESULTS: In the first-stage survey, 33 participants responded. Six main themes were identified: imaging interpretation and preoperative diagnosis, coordination of the surgical team, operative planning, real-time alert of hazards and complications, autonomous surgery, and postoperative management and follow-up. In the second stage, 100 participants responded. Responders somewhat agreed or strongly agreed about AI being used for imaging interpretation (62%), operative planning (82%), coordination of the surgical team (70%), real-time alert of hazards and complications (85%), and autonomous surgery (66%). The role of AI within postoperative management and follow-up was less agreeable (49%). CONCLUSIONS: This survey highlights that the majority of surgeons and the wider surgical team both agree and are comfortable with the application of AI within neurosurgery.
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Inteligencia Artificial / Actitud del Personal de Salud / Neurocirugia Tipo de estudio: Observational_studies / Prevalence_studies / Qualitative_research / Risk_factors_studies Límite: Adult / Female / Humans / Male / Middle aged Idioma: En Año: 2021 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Inteligencia Artificial / Actitud del Personal de Salud / Neurocirugia Tipo de estudio: Observational_studies / Prevalence_studies / Qualitative_research / Risk_factors_studies Límite: Adult / Female / Humans / Male / Middle aged Idioma: En Año: 2021 Tipo del documento: Article