View in EDS HTML Full Text PDF Full Text

A scoping review of artificial intelligence in medical education: BEME Guide No. 84.

Saved in:
Bibliographic Details
Title: A scoping review of artificial intelligence in medical education: BEME Guide No. 84.
Authors: Gordon, Morris1,2 mgordon@uclan.ac.uk, Daniel, Michelle3, Ajiboye, Aderonke1, Uraiby, Hussein4, Xu, Nicole Y.3, Bartlett, Rangana5, Hanson, Janice6, Haas, Mary7, Spadafore, Maxwell7, Grafton-Clarke, Ciaran8, Gasiea, Rayhan Yousef2, Michie, Colin1, Corral, Janet9, Kwan, Brian3, Dolmans, Diana10, Thammasitboon, Satid11
Source: Medical Teacher. Apr2024, Vol. 46 Issue 4, p446-470. 25p.
Subject Terms: *Policy sciences, *Medical education, *Diffusion of innovations, *Artificial intelligence, *Rating of students, *Educational technology, *Teaching, *Education research, *School admission, Medical protocols, Medical information storage & retrieval systems, Medical logic, Systematic reviews, MEDLINE, Evidence-based medicine, Online information services, Medical ethics
Geographic Terms: North America, Europe
Abstract: Artificial Intelligence (AI) is rapidly transforming healthcare, and there is a critical need for a nuanced understanding of how AI is reshaping teaching, learning, and educational practice in medical education. This review aimed to map the literature regarding AI applications in medical education, core areas of findings, potential candidates for formal systematic review and gaps for future research. This rapid scoping review, conducted over 16 weeks, employed Arksey and O'Malley's framework and adhered to STORIES and BEME guidelines. A systematic and comprehensive search across PubMed/MEDLINE, EMBASE, and MedEdPublish was conducted without date or language restrictions. Publications included in the review spanned undergraduate, graduate, and continuing medical education, encompassing both original studies and perspective pieces. Data were charted by multiple author pairs and synthesized into various thematic maps and charts, ensuring a broad and detailed representation of the current landscape. The review synthesized 278 publications, with a majority (68%) from North American and European regions. The studies covered diverse AI applications in medical education, such as AI for admissions, teaching, assessment, and clinical reasoning. The review highlighted AI's varied roles, from augmenting traditional educational methods to introducing innovative practices, and underscores the urgent need for ethical guidelines in AI's application in medical education. The current literature has been charted. The findings underscore the need for ongoing research to explore uncharted areas and address potential risks associated with AI use in medical education. This work serves as a foundational resource for educators, policymakers, and researchers in navigating AI's evolving role in medical education. A framework to support future high utility reporting is proposed, the FACETS framework. [ABSTRACT FROM AUTHOR]
Copyright of Medical Teacher is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Education Research Complete
Full text is not displayed to guests.
FullText Links:
  – Type: pdflink
Text:
  Availability: 1
Header DbId: ehh
DbLabel: Education Research Complete
An: 177037632
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: A scoping review of artificial intelligence in medical education: BEME Guide No. 84.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Gordon%2C+Morris%22">Gordon, Morris</searchLink><relatesTo>1,2</relatesTo><i> mgordon@uclan.ac.uk</i><br /><searchLink fieldCode="AR" term="%22Daniel%2C+Michelle%22">Daniel, Michelle</searchLink><relatesTo>3</relatesTo><br /><searchLink fieldCode="AR" term="%22Ajiboye%2C+Aderonke%22">Ajiboye, Aderonke</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Uraiby%2C+Hussein%22">Uraiby, Hussein</searchLink><relatesTo>4</relatesTo><br /><searchLink fieldCode="AR" term="%22Xu%2C+Nicole+Y%2E%22">Xu, Nicole Y.</searchLink><relatesTo>3</relatesTo><br /><searchLink fieldCode="AR" term="%22Bartlett%2C+Rangana%22">Bartlett, Rangana</searchLink><relatesTo>5</relatesTo><br /><searchLink fieldCode="AR" term="%22Hanson%2C+Janice%22">Hanson, Janice</searchLink><relatesTo>6</relatesTo><br /><searchLink fieldCode="AR" term="%22Haas%2C+Mary%22">Haas, Mary</searchLink><relatesTo>7</relatesTo><br /><searchLink fieldCode="AR" term="%22Spadafore%2C+Maxwell%22">Spadafore, Maxwell</searchLink><relatesTo>7</relatesTo><br /><searchLink fieldCode="AR" term="%22Grafton-Clarke%2C+Ciaran%22">Grafton-Clarke, Ciaran</searchLink><relatesTo>8</relatesTo><br /><searchLink fieldCode="AR" term="%22Gasiea%2C+Rayhan+Yousef%22">Gasiea, Rayhan Yousef</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AR" term="%22Michie%2C+Colin%22">Michie, Colin</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Corral%2C+Janet%22">Corral, Janet</searchLink><relatesTo>9</relatesTo><br /><searchLink fieldCode="AR" term="%22Kwan%2C+Brian%22">Kwan, Brian</searchLink><relatesTo>3</relatesTo><br /><searchLink fieldCode="AR" term="%22Dolmans%2C+Diana%22">Dolmans, Diana</searchLink><relatesTo>10</relatesTo><br /><searchLink fieldCode="AR" term="%22Thammasitboon%2C+Satid%22">Thammasitboon, Satid</searchLink><relatesTo>11</relatesTo>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22Medical+Teacher%22">Medical Teacher</searchLink>. Apr2024, Vol. 46 Issue 4, p446-470. 25p.
– Name: Subject
  Label: Subject Terms
  Group: Su
  Data: *<searchLink fieldCode="DE" term="%22Policy+sciences%22">Policy sciences</searchLink><br />*<searchLink fieldCode="DE" term="%22Medical+education%22">Medical education</searchLink><br />*<searchLink fieldCode="DE" term="%22Diffusion+of+innovations%22">Diffusion of innovations</searchLink><br />*<searchLink fieldCode="DE" term="%22Artificial+intelligence%22">Artificial intelligence</searchLink><br />*<searchLink fieldCode="DE" term="%22Rating+of+students%22">Rating of students</searchLink><br />*<searchLink fieldCode="DE" term="%22Educational+technology%22">Educational technology</searchLink><br />*<searchLink fieldCode="DE" term="%22Teaching%22">Teaching</searchLink><br />*<searchLink fieldCode="DE" term="%22Education+research%22">Education research</searchLink><br />*<searchLink fieldCode="DE" term="%22School+admission%22">School admission</searchLink><br /><searchLink fieldCode="DE" term="%22Medical+protocols%22">Medical protocols</searchLink><br /><searchLink fieldCode="DE" term="%22Medical+information+storage+%26+retrieval+systems%22">Medical information storage & retrieval systems</searchLink><br /><searchLink fieldCode="DE" term="%22Medical+logic%22">Medical logic</searchLink><br /><searchLink fieldCode="DE" term="%22Systematic+reviews%22">Systematic reviews</searchLink><br /><searchLink fieldCode="DE" term="%22MEDLINE%22">MEDLINE</searchLink><br /><searchLink fieldCode="DE" term="%22Evidence-based+medicine%22">Evidence-based medicine</searchLink><br /><searchLink fieldCode="DE" term="%22Online+information+services%22">Online information services</searchLink><br /><searchLink fieldCode="DE" term="%22Medical+ethics%22">Medical ethics</searchLink>
– Name: SubjectGeographic
  Label: Geographic Terms
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22North+America%22">North America</searchLink><br /><searchLink fieldCode="DE" term="%22Europe%22">Europe</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Artificial Intelligence (AI) is rapidly transforming healthcare, and there is a critical need for a nuanced understanding of how AI is reshaping teaching, learning, and educational practice in medical education. This review aimed to map the literature regarding AI applications in medical education, core areas of findings, potential candidates for formal systematic review and gaps for future research. This rapid scoping review, conducted over 16 weeks, employed Arksey and O'Malley's framework and adhered to STORIES and BEME guidelines. A systematic and comprehensive search across PubMed/MEDLINE, EMBASE, and MedEdPublish was conducted without date or language restrictions. Publications included in the review spanned undergraduate, graduate, and continuing medical education, encompassing both original studies and perspective pieces. Data were charted by multiple author pairs and synthesized into various thematic maps and charts, ensuring a broad and detailed representation of the current landscape. The review synthesized 278 publications, with a majority (68%) from North American and European regions. The studies covered diverse AI applications in medical education, such as AI for admissions, teaching, assessment, and clinical reasoning. The review highlighted AI's varied roles, from augmenting traditional educational methods to introducing innovative practices, and underscores the urgent need for ethical guidelines in AI's application in medical education. The current literature has been charted. The findings underscore the need for ongoing research to explore uncharted areas and address potential risks associated with AI use in medical education. This work serves as a foundational resource for educators, policymakers, and researchers in navigating AI's evolving role in medical education. A framework to support future high utility reporting is proposed, the FACETS framework. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Medical Teacher is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=ehh&AN=177037632
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1080/0142159X.2024.2314198
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 25
        StartPage: 446
    Subjects:
      – SubjectFull: Policy sciences
        Type: general
      – SubjectFull: Medical education
        Type: general
      – SubjectFull: Diffusion of innovations
        Type: general
      – SubjectFull: Artificial intelligence
        Type: general
      – SubjectFull: Rating of students
        Type: general
      – SubjectFull: Educational technology
        Type: general
      – SubjectFull: Teaching
        Type: general
      – SubjectFull: Education research
        Type: general
      – SubjectFull: School admission
        Type: general
      – SubjectFull: Medical protocols
        Type: general
      – SubjectFull: Medical information storage & retrieval systems
        Type: general
      – SubjectFull: Medical logic
        Type: general
      – SubjectFull: Systematic reviews
        Type: general
      – SubjectFull: MEDLINE
        Type: general
      – SubjectFull: Evidence-based medicine
        Type: general
      – SubjectFull: Online information services
        Type: general
      – SubjectFull: Medical ethics
        Type: general
      – SubjectFull: North America
        Type: general
      – SubjectFull: Europe
        Type: general
    Titles:
      – TitleFull: A scoping review of artificial intelligence in medical education: BEME Guide No. 84.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Gordon, Morris
      – PersonEntity:
          Name:
            NameFull: Daniel, Michelle
      – PersonEntity:
          Name:
            NameFull: Ajiboye, Aderonke
      – PersonEntity:
          Name:
            NameFull: Uraiby, Hussein
      – PersonEntity:
          Name:
            NameFull: Xu, Nicole Y.
      – PersonEntity:
          Name:
            NameFull: Bartlett, Rangana
      – PersonEntity:
          Name:
            NameFull: Hanson, Janice
      – PersonEntity:
          Name:
            NameFull: Haas, Mary
      – PersonEntity:
          Name:
            NameFull: Spadafore, Maxwell
      – PersonEntity:
          Name:
            NameFull: Grafton-Clarke, Ciaran
      – PersonEntity:
          Name:
            NameFull: Gasiea, Rayhan Yousef
      – PersonEntity:
          Name:
            NameFull: Michie, Colin
      – PersonEntity:
          Name:
            NameFull: Corral, Janet
      – PersonEntity:
          Name:
            NameFull: Kwan, Brian
      – PersonEntity:
          Name:
            NameFull: Dolmans, Diana
      – PersonEntity:
          Name:
            NameFull: Thammasitboon, Satid
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 04
              Text: Apr2024
              Type: published
              Y: 2024
          Identifiers:
            – Type: issn-print
              Value: 0142159X
          Numbering:
            – Type: volume
              Value: 46
            – Type: issue
              Value: 4
          Titles:
            – TitleFull: Medical Teacher
              Type: main
ResultId 1