NCT05168150

Testing the Efficacy of an Artificial Intelligence Real-Time Coaching SystemSystemSimulatioTraining of Medical Students

Completed NA Last updated 8 August 2022

What this trial tests

NA trial testing Experimental: Experimental Group - Intelligent Continuous Expertise Monitoring System group in Surgical Education in 98 participants. Completed in 3 May 2022.

Timeline

5 January 2022

Primary endpoint
3 May 2022

3 May 2022

Quick facts

Lead sponsor	McGill University
Phase	NA
Status	Completed
Study type	INTERVENTIONAL
Allocation	randomized
Design	parallel
Masking	double
Primary purpose	health services research
Enrollment	98
Start date	5 January 2022
Primary completion	3 May 2022
Estimated completion	3 May 2022
Sites	1 location across Canada

Drugs / interventions tested

• Experimental: Experimental Group - Intelligent Continuous Expertise Monitoring System group
• Experimental Group In-person expert-mediated instruction group

Conditions studied

• Surgical Education — all drugs for Surgical Education →

Sponsor

McGill University

Who can join

18 and older, any sex, with Surgical Education. Patients with the condition only — healthy volunteers not accepted.

Sponsor's own description

Background:

Trainees learn surgical technical skills through apprenticeship model working closely with surgeons and given increased responsibility in patient cases under expert supervision. However, factors such as surgeons' busy schedule, number of available patient cases, patient safety and lack of objectivity and standardization in training pose strong limitations. Virtual reality surgical simulators integrated with artificial intelligence (AI) systems provide a standardized realistic simulation environment and detailed performance data that allows accurate quantitation of surgical skills and tailored feedback. These platforms make repetitive practice of surgical skills possible in a risk-free environment.

The Intelligent Continuous Monitoring System (ICEMS), a deep learning application integrated in NeuroVR simulation platform, was developed to assess surgical performance continuously in 0.2 second intervals and provide coaching and risk detection. Although a predictive validity for assessment module was provided previously, the effectiveness of real-time coaching and risk detection ability with this AI system remains to be explored.

The objective of this study is to compare the error-oriented intelligent feedback provided by the ICEMS to in-person expert instruction in surgical simulation training by monitoring the improvement of medical student technical skills on a series of virtual reality tumor resection tasks.

Publications & conference data

3 peer-reviewed publications reference this trial (live from Europe PMC):

1. Effect of Artificial Intelligence Tutoring vs Expert Instruction on Learning Simulated Surgical Skills Among Medical Students: A Randomized Clinical Trial.
   Fazlollahi AM, Bakhaidar M, Alsayegh A, Yilmaz R, et al · · 2022 · cited 114× · PMID 35191972 · DOI 10.1001/jamanetworkopen.2021.49008
2. Continuous monitoring of surgical bimanual expertise using deep neural networks in virtual reality simulation.
   Yilmaz R, Winkler-Schwartz A, Mirchi N, Reich A, et al · · 2022 · cited 25× · PMID 35473961 · DOI 10.1038/s41746-022-00596-8
3. Real-Time multifaceted artificial intelligence vs In-Person instruction in teaching surgical technical skills: a randomized controlled trial.
   Yilmaz R, Bakhaidar M, Alsayegh A, Abou Hamdan N, et al · · 2024 · cited 14× · PMID 38956112 · DOI 10.1038/s41598-024-65716-8