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Application of artificial intelligence in medical education: A meta-ethnographic synthesis.

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Title: Application of artificial intelligence in medical education: A meta-ethnographic synthesis.
Authors: Li, Wei1, Shi, Hai-Yan2, Chen, Xiao-Ling3, Lan, Jian-Zeng1, Rehman, Attiq-Ur1,4, Ge, Meng-Wei1, Shen, Lu-Ting1, Hu, Fei-Hong1, Jia, Yi-Jie1, Li, Xiao-Min5 jsmmxm@163.com, Chen, Hong-Lin1 honglinyjs@126.com
Source: Medical Teacher. Jul2025, Vol. 47 Issue 7, p1168-1181. 14p.
Subject Terms: *Medical education, *Qualitative research, *Artificial intelligence, *Curriculum planning, Ethnology research, CINAHL database, Systematic reviews, MEDLINE, Thematic analysis, Meta-synthesis, Online information services, Quality assurance, Psychology information storage & retrieval systems
Abstract: Background: With the advancement of Artificial Intelligence (AI), it has had a profound impact on medical education. Understanding the advantages and issues of AI in medical education, providing guidance for educators, and overcoming challenges in the implementation process is particularly important. Objective: The objective of this study is to explore the current state of AI applications in medical education. Methods: A systematic search was conducted across databases such as PsycINFO, CINAHL, Scopus, PubMed, and Web of Science to identify relevant studies. The Critical Appraisal Skills Programme (CASP) was employed for the quality assessment of these studies, followed by thematic synthesis to analyze the themes from the included research. Results: Ultimately, 21 studies were identified, establishing four themes: (1) Shaping the Future: Current Trends in AI within Medical Education; (2) Advancing Medical Instruction: The Transformative Power of AI; (3) Navigating the Ethical Landscape of AI in Medical Education; (4) Fostering Synergy: Integrating Artificial Intelligence in Medical Curriculum. Conclusion: Artificial intelligence's role in medical education, while not yet extensive, is impactful and promising. Despite challenges, including ethical concerns over privacy, responsibility, and humanistic care, future efforts should focus on integrating AI through targeted courses to improve educational quality. [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.)
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  Data: Application of artificial intelligence in medical education: A meta-ethnographic synthesis.
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  Data: <searchLink fieldCode="AR" term="%22Li%2C+Wei%22">Li, Wei</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Shi%2C+Hai-Yan%22">Shi, Hai-Yan</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AR" term="%22Chen%2C+Xiao-Ling%22">Chen, Xiao-Ling</searchLink><relatesTo>3</relatesTo><br /><searchLink fieldCode="AR" term="%22Lan%2C+Jian-Zeng%22">Lan, Jian-Zeng</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Rehman%2C+Attiq-Ur%22">Rehman, Attiq-Ur</searchLink><relatesTo>1,4</relatesTo><br /><searchLink fieldCode="AR" term="%22Ge%2C+Meng-Wei%22">Ge, Meng-Wei</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Shen%2C+Lu-Ting%22">Shen, Lu-Ting</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Hu%2C+Fei-Hong%22">Hu, Fei-Hong</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Jia%2C+Yi-Jie%22">Jia, Yi-Jie</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Li%2C+Xiao-Min%22">Li, Xiao-Min</searchLink><relatesTo>5</relatesTo><i> jsmmxm@163.com</i><br /><searchLink fieldCode="AR" term="%22Chen%2C+Hong-Lin%22">Chen, Hong-Lin</searchLink><relatesTo>1</relatesTo><i> honglinyjs@126.com</i>
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  Data: <searchLink fieldCode="JN" term="%22Medical+Teacher%22">Medical Teacher</searchLink>. Jul2025, Vol. 47 Issue 7, p1168-1181. 14p.
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  Data: *<searchLink fieldCode="DE" term="%22Medical+education%22">Medical education</searchLink><br />*<searchLink fieldCode="DE" term="%22Qualitative+research%22">Qualitative research</searchLink><br />*<searchLink fieldCode="DE" term="%22Artificial+intelligence%22">Artificial intelligence</searchLink><br />*<searchLink fieldCode="DE" term="%22Curriculum+planning%22">Curriculum planning</searchLink><br /><searchLink fieldCode="DE" term="%22Ethnology+research%22">Ethnology research</searchLink><br /><searchLink fieldCode="DE" term="%22CINAHL+database%22">CINAHL database</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="%22Thematic+analysis%22">Thematic analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Meta-synthesis%22">Meta-synthesis</searchLink><br /><searchLink fieldCode="DE" term="%22Online+information+services%22">Online information services</searchLink><br /><searchLink fieldCode="DE" term="%22Quality+assurance%22">Quality assurance</searchLink><br /><searchLink fieldCode="DE" term="%22Psychology+information+storage+%26+retrieval+systems%22">Psychology information storage & retrieval systems</searchLink>
– Name: Abstract
  Label: Abstract
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  Data: Background: With the advancement of Artificial Intelligence (AI), it has had a profound impact on medical education. Understanding the advantages and issues of AI in medical education, providing guidance for educators, and overcoming challenges in the implementation process is particularly important. Objective: The objective of this study is to explore the current state of AI applications in medical education. Methods: A systematic search was conducted across databases such as PsycINFO, CINAHL, Scopus, PubMed, and Web of Science to identify relevant studies. The Critical Appraisal Skills Programme (CASP) was employed for the quality assessment of these studies, followed by thematic synthesis to analyze the themes from the included research. Results: Ultimately, 21 studies were identified, establishing four themes: (1) Shaping the Future: Current Trends in AI within Medical Education; (2) Advancing Medical Instruction: The Transformative Power of AI; (3) Navigating the Ethical Landscape of AI in Medical Education; (4) Fostering Synergy: Integrating Artificial Intelligence in Medical Curriculum. Conclusion: Artificial intelligence's role in medical education, while not yet extensive, is impactful and promising. Despite challenges, including ethical concerns over privacy, responsibility, and humanistic care, future efforts should focus on integrating AI through targeted courses to improve educational quality. [ABSTRACT FROM AUTHOR]
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  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.)
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RecordInfo BibRecord:
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      – Type: doi
        Value: 10.1080/0142159X.2024.2418936
    Languages:
      – Code: eng
        Text: English
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        PageCount: 14
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    Subjects:
      – SubjectFull: Medical education
        Type: general
      – SubjectFull: Qualitative research
        Type: general
      – SubjectFull: Artificial intelligence
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      – SubjectFull: Curriculum planning
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      – SubjectFull: Ethnology research
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      – SubjectFull: Psychology information storage & retrieval systems
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              Text: Jul2025
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