Exploring the roles of artificial intelligence in surgical education: A scoping review - 20/06/22

Doi : 10.1016/j.amjsurg.2021.11.023

Elif Bilgic ^a, Andrew Gorgy ^a, Alison Yang ^a, Michelle Cwintal ^a, Hamed Ranjbar ^a, Kalin Kahla ^a, Dheeksha Reddy ^a, Kexin Li ^a, Helin Ozturk ^a, Eric Zimmermann ^a, Andrea Quaiattini ^b,^c, Samira Abbasgholizadeh-Rahimi ^d,^e,^f,^g, Dan Poenaru ^c,^h, Jason M. Harley ^a,^c,^i,^j,^⁎
^a Department of Surgery, McGill University, Montreal, Quebec, Canada
^b Schulich Library of Physical Sciences, Life Sciences, and Engineering, McGill University, Canada
^c Institute of Health Sciences Education, McGill University, Montreal, Quebec, Canada
^d Department of Family Medicine, McGill University, Montreal, Quebec, Canada
^e Department of Electrical and Computer Engineering, McGill University, Montreal, Canada
^f Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal, Canada
^g Mila Quebec AI Institute, Montreal, Canada
^h Department of Pediatric Surgery, McGill University, Canada
ⁱ Research Institute of the McGill University Health Centre, Montreal, Quebec, Canada
^j Steinberg Centre for Simulation and Interactive Learning, McGill University, Montreal, Quebec, Canada

^∗Corresponding author. Department of Surgery, Faculty of Medicine, McGill University, Montreal General Hospital, 1650 Cedar Ave, R1.112, Montreal, QC, H3G 1A4, Canada.Department of SurgeryFaculty of MedicineMcGill UniversityMontreal General Hospital1650 Cedar Ave, R1.112MontrealQCH3G 1A4Canada

Abstract

Background

Technology-enhanced teaching and learning, including Artificial Intelligence (AI) applications, has started to evolve in surgical education. Hence, the purpose of this scoping review is to explore the current and future roles of AI in surgical education.

Methods

Nine bibliographic databases were searched from January 2010 to January 2021. Full-text articles were included if they focused on AI in surgical education.

Results

Out of 14,008 unique sources of evidence, 93 were included. Out of 93, 84 were conducted in the simulation setting, and 89 targeted technical skills. Fifty-six studies focused on skills assessment/classification, and 36 used multiple AI techniques. Also, increasing sample size, having balanced data, and using AI to provide feedback were major future directions mentioned by authors.

Conclusions

AI can help optimize the education of trainees and our results can help educators and researchers identify areas that need further investigation.

Le texte complet de cet article est disponible en PDF.

Highlights

•	Current AI studies target simulation setting and technical skills.
•	Majority focus on skill classification and performance assessment.
•	Majority used multiple metrics and AI techniques.
•	Need studies with bigger sample size and balanced data.
•	Need to explore using AI to provide feedback to trainees in clinical setting.

Le texte complet de cet article est disponible en PDF.

Keywords : Artificial intelligence, Surgical education, Assessment, Training

Plan

Export

Vol 224 - N° 1PA

P. 205-216 - juillet 2022 Retour au numéro

Article précédent

Management of rhabdomyolysis: A practice management guideline from the Eastern Association for the Surgery of Trauma
Jaswin S. Sawhney, George Kasotakis, Anna Goldenberg, Stuart Abramson, Christopher Dodgion, Nimitt Patel, Mansoor Khan, John J. Como

| Article suivant

Colonic stenting for malignant obstructions-A review of current indications and outcomes
Amelie Lueders, Gabie Ong, Peter Davis, Jonathan Weyerbacher, Jonathan Saxe

Bienvenue sur EM-consulte, la référence des professionnels de santé.
L’accès au texte intégral de cet article nécessite un abonnement.

Déjà abonné à cette revue ?

connectez-vous ou créez un compte

Exploring the roles of artificial intelligence in surgical education: A scoping review - 20/06/22

Abstract

Background

Methods

Results

Conclusions

Highlights

Plan

Export citations

Fichier

Contenu

Accès rapides

Mon compte

Aide & support

Plateformes Elsevier Masson

Déclaration CNIL