Department of Urology, Trakya University School of Medicine, Edirne, Turkey.
Department of Urology, Meram School of Medicine, Necmettin Erbakan University, Konya, Turkey.
Surg Innov. 2024 Aug;31(4):415-423. doi: 10.1177/15533506241248239. Epub 2024 Apr 17.
To examine the artificial intelligence (AI) tools currently being studied in modern medical education, and critically evaluate the level of validation and the quality of evidence presented in each individual study.
This review (PROSPERO ID: CRD42023410752) was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) statement. A database search was conducted using PubMed, Embase, and Cochrane Library. Articles written in the English language between 2000 and March 2023 were reviewed retrospectively using the MeSH Terms "AI" and "medical education" A total of 4642 potentially relevant studies were found.
After a thorough screening process, 36 studies were included in the final analysis. These studies consisted of 26 quantitative studies and 10 studies investigated the development and validation of AI tools. When examining the results of studies in which Support vector machines (SVMs) were employed, it has demonstrated high accuracy in assessing students' experiences, diagnosing acute abdominal pain, classifying skilled and novice participants, and evaluating surgical training levels. Particularly in the comparison of surgical skill levels, it has achieved an accuracy rate of over 92%.
AI tools demonstrated effectiveness in improving practical skills, diagnosing diseases, and evaluating student performance. However, further research with rigorous validation is required to identify the most effective AI tools for medical education.
本研究旨在考察当前医学教育中应用的人工智能（AI）工具，并对每项研究中验证水平和证据质量进行批判性评估。
本综述（PROSPERO 注册号：CRD42023410752）根据系统评价和荟萃分析的首选报告项目（PRISMA）声明进行。通过 PubMed、Embase 和 Cochrane Library 数据库检索，检索年限为 2000 年至 2023 年 3 月，使用“AI”和“医学教育”的 MeSH 术语回顾性检索英文文章。共检索到 4642 篇可能相关的研究。
经过彻底筛选，最终有 36 项研究纳入分析。这些研究包括 26 项定量研究和 10 项 AI 工具的开发和验证研究。当检查使用支持向量机（SVM）的研究结果时，其在评估学生体验、诊断急性腹痛、区分熟练和非熟练参与者以及评估手术培训水平方面具有较高的准确性。特别是在比较手术技能水平方面，其准确性超过 92%。
AI 工具在提高实践技能、诊断疾病和评估学生表现方面具有有效性。然而，需要进一步进行严格验证的研究，以确定最有效的医学教育 AI 工具。
