Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
346 Transforming ENT Induction: Assessing the Impact of an AI Avatar Delivered Induction Course on Trainee Confidence at John Radcliffe Hospital, Oxford
0
Zitationen
3
Autoren
2024
Jahr
Abstract
Abstract In the evolving landscape of surgical education, innovative methods are crucial for enhancing trainee proficiency. This study evaluates the impact of an AI Avatar delivered ENT induction course, which utilises interactive video and image technology, on changes in trainees' confidence in key ENT skills, and as well as the role of AI tutors in this process. We analysed pre- and post-course feedback from participants enrolled in the entinduction.co.uk SHO induction program from the John Radcliffe Hospital, Oxford, ENT department. The primary focus was on changes in confidence across seven key ENT skills. Paired t-tests assessed the statistical significance of these changes. There were 24 participants. 8 GP Trainees, 10 FY2s, 2 Core surgical trainees and 4 Clinical Fellows. All areas showed statistically significant improvements in confidence post-course (p < 0.05). The highest increases were observed in identifying normal endoscopic upper aerodigestive tract anatomy (Δ=+3.87), identifying endoscopic pathology (Δ=+3.83), managing ENT emergencies (Δ=+3.67), triaging ENT referrals (Δ=+3.63) and managing upper airway obstruction (Δ=+3.27). Notable increases were also present in identifying ear pathology on otoscopy (Δ=+2.90) and identifying normal ear anatomy on Otoscopy (Δ=+2.88). Overall course quality was highly rated (mean=8.45/10), with a strong recommendation level from participants. The AI tutors were positively received, with varying impact on learning and retention. The ENT induction course significantly boosted participants' confidence, affirming the effectiveness of its curriculum and pedagogical approach. The integration of AI tutors was well-received, highlighting their potential in enhancing surgical education. These results advocate for the continued adoption of innovative instructional strategies in surgical training programs.
Ähnliche Arbeiten
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
2019 · 8.260 Zit.
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
2019 · 8.116 Zit.
High-performance medicine: the convergence of human and artificial intelligence
2018 · 7.493 Zit.
Proceedings of the 19th International Joint Conference on Artificial Intelligence
2005 · 5.776 Zit.
Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI)
2018 · 5.438 Zit.