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Innovations in surgical training: exploring the role of artificial intelligence and large language models (LLM)
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 m...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Colégio Brasileiro de Cirurgiões
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10508667/ https://www.ncbi.nlm.nih.gov/pubmed/37646729 http://dx.doi.org/10.1590/0100-6991e-20233605-en |
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author | VARAS, JULIAN CORONEL, BRANDON VALENCIA VILLAGRÁN, IGNACIO ESCALONA, GABRIEL HERNANDEZ, ROCIO SCHUIT, GREGORY DURÁN, VALENTINA LAGOS-VILLASECA, ANTONIA JARRY, CRISTIAN NEYEM, ANDRES ACHURRA, PABLO |
author_facet | VARAS, JULIAN CORONEL, BRANDON VALENCIA VILLAGRÁN, IGNACIO ESCALONA, GABRIEL HERNANDEZ, ROCIO SCHUIT, GREGORY DURÁN, VALENTINA LAGOS-VILLASECA, ANTONIA JARRY, CRISTIAN NEYEM, ANDRES ACHURRA, PABLO |
author_sort | VARAS, JULIAN |
collection | PubMed |
description | 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. . |
format | Online Article Text |
id | pubmed-10508667 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Colégio Brasileiro de Cirurgiões |
record_format | MEDLINE/PubMed |
spelling | pubmed-105086672023-09-21 Innovations in surgical training: exploring the role of artificial intelligence and large language models (LLM) VARAS, JULIAN CORONEL, BRANDON VALENCIA VILLAGRÁN, IGNACIO ESCALONA, GABRIEL HERNANDEZ, ROCIO SCHUIT, GREGORY DURÁN, VALENTINA LAGOS-VILLASECA, ANTONIA JARRY, CRISTIAN NEYEM, ANDRES ACHURRA, PABLO Rev Col Bras Cir Education 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. . Colégio Brasileiro de Cirurgiões 2023-08-14 /pmc/articles/PMC10508667/ /pubmed/37646729 http://dx.doi.org/10.1590/0100-6991e-20233605-en Text en © 2023 Revista do Colégio Brasileiro de Cirurgiões https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License |
spellingShingle | Education VARAS, JULIAN CORONEL, BRANDON VALENCIA VILLAGRÁN, IGNACIO ESCALONA, GABRIEL HERNANDEZ, ROCIO SCHUIT, GREGORY DURÁN, VALENTINA LAGOS-VILLASECA, ANTONIA JARRY, CRISTIAN NEYEM, ANDRES ACHURRA, PABLO Innovations in surgical training: exploring the role of artificial intelligence and large language models (LLM) |
title | Innovations in surgical training: exploring the role of artificial intelligence and large language models (LLM) |
title_full | Innovations in surgical training: exploring the role of artificial intelligence and large language models (LLM) |
title_fullStr | Innovations in surgical training: exploring the role of artificial intelligence and large language models (LLM) |
title_full_unstemmed | Innovations in surgical training: exploring the role of artificial intelligence and large language models (LLM) |
title_short | Innovations in surgical training: exploring the role of artificial intelligence and large language models (LLM) |
title_sort | innovations in surgical training: exploring the role of artificial intelligence and large language models (llm) |
topic | Education |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10508667/ https://www.ncbi.nlm.nih.gov/pubmed/37646729 http://dx.doi.org/10.1590/0100-6991e-20233605-en |
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