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The Global Use of Artificial Intelligence in the Undergraduate Medical Curriculum: A Systematic Review

Artificial intelligence (AI) is a rapidly advancing technology that has the potential to revolutionize medical education. AI can provide personalized learning experiences, assist with student assessment, and aid in the integration of pre-clinical and clinical curricula. Despite the potential benefit...

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Autores principales: Varma, Jonny R, Fernando, Sherwin, Ting, Brian Y, Aamir, Shahrukh, Sivaprakasam, Rajesh
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cureus 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10309075/
https://www.ncbi.nlm.nih.gov/pubmed/37398823
http://dx.doi.org/10.7759/cureus.39701
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author Varma, Jonny R
Fernando, Sherwin
Ting, Brian Y
Aamir, Shahrukh
Sivaprakasam, Rajesh
author_facet Varma, Jonny R
Fernando, Sherwin
Ting, Brian Y
Aamir, Shahrukh
Sivaprakasam, Rajesh
author_sort Varma, Jonny R
collection PubMed
description Artificial intelligence (AI) is a rapidly advancing technology that has the potential to revolutionize medical education. AI can provide personalized learning experiences, assist with student assessment, and aid in the integration of pre-clinical and clinical curricula. Despite the potential benefits, there is a paucity of literature investigating the use of AI in undergraduate medical education. This study aims to evaluate the role of AI in undergraduate medical curricula worldwide and compare AI to current teaching and assessment methods. This systematic review was conducted using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) reporting guidelines. Texts unavailable in English were excluded alongside those not focused on medical students alone or with little mention of AI. The key search terms were “undergraduate medical education,” “medical students,” “medical education,” and “artificial intelligence.” The methodological rigor of each study was assessed using the Medical Education Research Study Quality Instrument (MERSQI). A total of 36 articles were screened from 700 initial articles, of which 11 were deemed eligible. These were categorized into the following three domains: teaching (n = 6), assessing (n = 3), and trend spotting (n = 2). AI was shown to be highly accurate in studies that directly tested its ability. The mean overall MERSQI score for all selected papers was 10.5 (standard deviation = 2.3; range = 6 to 15.5) falling below the expected score of 10.7 due to notable weaknesses in study design, sampling methods, and study outcomes. AI performance was synergized with human involvement suggesting that AI would be best employed as a supplement to undergraduate medical curricula. Studies directly comparing AI to current teaching methods demonstrated favorable performance. While shown to have a promising role, there remains a limited number of studies in the field, and further research is needed to refine and establish clear foundations to assist in its development.
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spelling pubmed-103090752023-06-30 The Global Use of Artificial Intelligence in the Undergraduate Medical Curriculum: A Systematic Review Varma, Jonny R Fernando, Sherwin Ting, Brian Y Aamir, Shahrukh Sivaprakasam, Rajesh Cureus Medical Education Artificial intelligence (AI) is a rapidly advancing technology that has the potential to revolutionize medical education. AI can provide personalized learning experiences, assist with student assessment, and aid in the integration of pre-clinical and clinical curricula. Despite the potential benefits, there is a paucity of literature investigating the use of AI in undergraduate medical education. This study aims to evaluate the role of AI in undergraduate medical curricula worldwide and compare AI to current teaching and assessment methods. This systematic review was conducted using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) reporting guidelines. Texts unavailable in English were excluded alongside those not focused on medical students alone or with little mention of AI. The key search terms were “undergraduate medical education,” “medical students,” “medical education,” and “artificial intelligence.” The methodological rigor of each study was assessed using the Medical Education Research Study Quality Instrument (MERSQI). A total of 36 articles were screened from 700 initial articles, of which 11 were deemed eligible. These were categorized into the following three domains: teaching (n = 6), assessing (n = 3), and trend spotting (n = 2). AI was shown to be highly accurate in studies that directly tested its ability. The mean overall MERSQI score for all selected papers was 10.5 (standard deviation = 2.3; range = 6 to 15.5) falling below the expected score of 10.7 due to notable weaknesses in study design, sampling methods, and study outcomes. AI performance was synergized with human involvement suggesting that AI would be best employed as a supplement to undergraduate medical curricula. Studies directly comparing AI to current teaching methods demonstrated favorable performance. While shown to have a promising role, there remains a limited number of studies in the field, and further research is needed to refine and establish clear foundations to assist in its development. Cureus 2023-05-30 /pmc/articles/PMC10309075/ /pubmed/37398823 http://dx.doi.org/10.7759/cureus.39701 Text en Copyright © 2023, Varma et al. https://creativecommons.org/licenses/by/3.0/This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Medical Education
Varma, Jonny R
Fernando, Sherwin
Ting, Brian Y
Aamir, Shahrukh
Sivaprakasam, Rajesh
The Global Use of Artificial Intelligence in the Undergraduate Medical Curriculum: A Systematic Review
title The Global Use of Artificial Intelligence in the Undergraduate Medical Curriculum: A Systematic Review
title_full The Global Use of Artificial Intelligence in the Undergraduate Medical Curriculum: A Systematic Review
title_fullStr The Global Use of Artificial Intelligence in the Undergraduate Medical Curriculum: A Systematic Review
title_full_unstemmed The Global Use of Artificial Intelligence in the Undergraduate Medical Curriculum: A Systematic Review
title_short The Global Use of Artificial Intelligence in the Undergraduate Medical Curriculum: A Systematic Review
title_sort global use of artificial intelligence in the undergraduate medical curriculum: a systematic review
topic Medical Education
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10309075/
https://www.ncbi.nlm.nih.gov/pubmed/37398823
http://dx.doi.org/10.7759/cureus.39701
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