人工智能辅助教学在医学教育中应用效果的Meta分析

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【中图分类号】G64 【文献标识码】A

AMeta-analysisof theapplicationeffect of artificial intelligence-assisted teachinginmedicaleducation

WEI Wei1#，LUO Gaomeng1#，LIU Runming1，LIU Sha²，LI Xiang1

1.Department of Neurosurgery， Zhongnan Hospital of Wuhan University， Wuhan 43o071， China

2.DepartmentofGeneralPractice，ZhongnanHospitalofWuhanUniversity，Wuhan43o71，China

#Co -first authors： WEI Wei and LUO Gaomeng

Correspondingauthors：WEI Wei，Email： wei.wei@whu.edu.cn;LI Xiang，Email： li.xiang@whu.edu.cr

【Abstract】 Objective To evaluate the effectiveness of artificial intelligence （AI）-assisted teaching in medical education through Meta-analysis.Methods PubMed， Web of Science，Embase， Wanfang， CNKI，and VIP databases were searched from database creation to April 1，2025， to identify relevant studies on the application of AI-assisted teaching in medical education.The risk of bias was assessed using the Cochrane Collaboration's tool for assessing risk of bias.Meta-analysis Was performed using R software. Heterogeneity tests， subgroup analyses， and sensitivity analyses were used to verify the robustness of the results.Results A total of 17 randomized controlled trials were included.Compared with traditional teaching，AI-assisted teaching significantly improved medical education participants' theoretical scores [SMD=1.35 P 95% CI （0.78，1.92）]， practical/operational skills [SMD =2.45 ， 95%CI （0.89，4.02）]，and teaching satisfaction [RR =1.39 ， 95%CI （1.20，1.61）]. The differences were statistically significant （P<0.05） . Subgroup analysis showed that， compared with traditional teaching，AI-assisted medical education improved theoretical performance acrossdiffrent medical education groups （junior college students， undergraduate students， graduate students， and physicians）and practical/operational skills across some groups （junior college students，undergraduate students，and physicians）.Sensitivity analysis showed robust results， except for publication bias in theoretical performance，and the conclusions were unchanged after trimming and filling corection. Conclusion AI can effectively empower medical education，significantly improving learning outcomes and teaching satisfaction，and contributing to the cultivation of clinical medical talent.

【Keywords】Artificial intelligence; Traditional teaching; Medical education; Meta-analysis

医学教育作为医疗卫生事业发展的基石，承担着培育复合型医疗人才的关键职责。（剩余12035字）