Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
COMPARING THE EFFICIENCY OF A REAL-TIME ARTIFICIAL INTELLIGENCE INSTRUCTOR TO HUMAN EXPERT INSTRUCTORS IN SIMULATED SURGICAL TECHNICAL SKILLS TRAINING– A RANDOMIZED CONTROLLED TRIAL
3
Zitationen
8
Autoren
2023
Jahr
Abstract
Abstract BTFC travel award recipient Artificial intelligence systems provide risk-free training on realistically simulated patient cases and objective assessment of surgical technical skills. This randomized controlled study compared a real-time intelligent tutoring system in technical skills learning with human expert instructor-mediated training. METHODS: Ninety-eight medical students performed six simulated brain tumor resections. Participants were randomly allocated into (1)no-real-time feedback, (2)real-time intelligent instruction, and (3)in- person human instruction. All students performed the first repetition without receiving feedback (baseline). Group-1 received visual feedback only after each procedure based on expert benchmarks. Group-2 was instructed by the intelligent system in real-time. After each task, the students were shown their error-video clips generated by this system alongside expert-level demonstrations on how to improve. Group-3 was instructed by human instructors during the tasks. After each task, instructors summarized the areas of improvement and demonstrated correction techniques. Participant performance was scored by the intelligent system and also by blinded experts using OSATS scores. The performance score was compared within groups and between groups to compare learning. RESULTS: Compared to baseline performance, Group-2 and Group-3 significantly improved in the performance score by the third and second repetition, respectively (p<0.01, p=0.01). The between-groups comparison demonstrated that Group-2 scored significantly higher than Group-3 in the fifth repetition (p<0.01). Group-2 achieved significantly higher OSATS scores than Group-1 in the sixth task. CONCLUSIONS: Artificial intelligence may facilitate trainee learning by providing equally or more efficient learning when compared to human instruction. These systems may aid in developing competency-based standardized curricula in surgical training.
Ähnliche Arbeiten
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
2019 · 8.197 Zit.
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
2019 · 8.047 Zit.
High-performance medicine: the convergence of human and artificial intelligence
2018 · 7.410 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 · 5.410 Zit.