Evidence map›Paper›PMID 37646729›Full record

ArticleRevista do Colegio Brasileiro de Cirurgioes2023

Innovations in surgical training: exploring the role of artificial intelligence and large language models (LLM).

Julian Varas, Brandon Valencia Coronel, Ignacio Villagrán, Gabriel Escalona, Rocio Hernandez, Gregory Schuit, Valentina Durán, Antonia Lagos-Villaseca, Cristian Jarry, Andres Neyem and 1 more

Abstract read
In one paragraph

Article in Revista do Colegio Brasileiro de Cirurgioes, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

28 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Artificial Intelligence Competencies and Educational Needs Among ERNICA Members: Results of a Multinational Survey.European journal of pediatric surgery : official journal of Austrian Association of Pediatric Surgery ... [et al] = Zeitschrift fur Kinderchirurgie · 2026
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  14. Design and Performance of a Neurosurgery Assisting Device.Biomimetics (Basel, Switzerland) · 2025
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  18. American Academy of Otolaryngology-Head and Neck Surgery (AAO-HNS) Report on Artificial Intelligence.Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery · 2025
    Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Julian Varas- Pontificia Universidad Católica de Chile, Experimental Surgery and Simulation Center, Department of Digestive Surgery - Santiago - Región Metropolitana - Chile.ORCID http://orcid.org/0000-0003-4890-9937
Brandon Valencia Coronel- Pontificia Universidad Católica de Chile, Experimental Surgery and Simulation Center, Department of Digestive Surgery - Santiago - Región Metropolitana - Chile.ORCID http://orcid.org/0000-0003-4231-4465
Ignacio Villagrán- Pontificia Universidad Católica de Chile, Carrera de Kinesiología, Departamento de Ciencias de la Salud, Facultad de Medicina - Santiago - Región Metropolitana - Chile.ORCID http://orcid.org/0000-0003-3130-8326
Gabriel Escalona- Pontificia Universidad Católica de Chile, Experimental Surgery and Simulation Center, Department of Digestive Surgery - Santiago - Región Metropolitana - Chile.ORCID http://orcid.org/0000-0001-8733-3614
Rocio Hernandez- Pontificia Universidad Católica de Chile, Computer Science Department, School of Engineering - Santiago - Región Metropolitana - Chile.ORCID http://orcid.org/0000-0003-4677-2519
Gregory Schuit- Pontificia Universidad Católica de Chile, Computer Science Department, School of Engineering - Santiago - Región Metropolitana - Chile.ORCID http://orcid.org/0000-0002-7219-9915
Valentina Durán- Pontificia Universidad Católica de Chile, Experimental Surgery and Simulation Center, Department of Digestive Surgery - Santiago - Región Metropolitana - Chile.ORCID http://orcid.org/0000-0002-0476-7415
Antonia Lagos-Villaseca- Pontificia Universidad Católica de Chile, Department of Otolaryngology - Santiago - Región Metropolitana - Chile.ORCID http://orcid.org/0000-0002-2579-5474
Cristian Jarry- Pontificia Universidad Católica de Chile, Experimental Surgery and Simulation Center, Department of Digestive Surgery - Santiago - Región Metropolitana - Chile.ORCID http://orcid.org/0000-0003-3548-4909
Andres Neyem- Pontificia Universidad Católica de Chile, Computer Science Department, School of Engineering - Santiago - Región Metropolitana - Chile.ORCID http://orcid.org/0000-0002-5734-722X
Pablo Achurra- Pontificia Universidad Católica de Chile, Experimental Surgery and Simulation Center, Department of Digestive Surgery - Santiago - Región Metropolitana - Chile.ORCID http://orcid.org/0000-0001-6803-423X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The landscape of surgical training is rapidly evolving with the advent of artificial intelligence (AI) and its integration into education and simulation. This manuscript aims to explore the potential applications and benefits of AI-assisted surgical training, particularly the use of large language models (LLMs), in enhancing communication, personalizing feedback, and promoting skill development. We discuss the advancements in simulation-based training, AI-driven assessment tools, video-based assessment systems, virtual reality (VR) and augmented reality (AR) platforms, and the potential role of LLMs in the transcription, translation, and summarization of feedback. Despite the promising opportunities presented by AI integration, several challenges must be addressed, including accuracy and reliability, ethical and privacy concerns, bias in AI models, integration with existing training systems, and training and adoption of AI-assisted tools. By proactively addressing these challenges and harnessing the potential of AI, the future of surgical training may be reshaped to provide a more comprehensive, safe, and effective learning experience for trainees, ultimately leading to better patient outcomes. .

Indexed as

Artificial IntelligenceLanguageComputer SimulationHumansLearningReproducibility of Results

Identifiers

PMID37646729
PMCPMC10508667

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.