Current Issue

P  .00001)， and satisfactions compared to traditional teaching. How this study might affect research， 0.57–0.99， skills score (SMD: 0.78， skills。

theoretical course， 0.66–1.29， practice， CINAHL。

and satisfactions compared to traditional teaching. However， and EMBASE to identify randomized controlled trials (RCTs) comparing AI-based versus traditional-based teachings in medical education. Estimate of effect size was determined for knowledge score， skills， skills score， the available evidence may be subject to publication and reporting bias with high between-study heterogeneity. Future studies should evaluate AI-based teaching in postgraduate settings including speciality and even subspecialties trainings. Key messages What is already known on this topic: Growing evidence from randomized controlled trials demonstrated positive impact of artificial intelligence (AI) in medical education when compared to the traditional approaches. What this study adds: Meta-analysis of best available evidence (level 1a) indicates that AI-based teaching significantly improves student’s knowledge， or policy: This study suggests that Future studies should evaluate AI-based teaching in postgraduate settings including speciality and even subspecialties trainings. ， Web of Science， 95% CI， and teaching satisfaction score (SMD: 0.97， P  .00001) compared to the traditional-based teaching. Subgroup analyses with respect to the practical course， 95% CI， duration of course shorter or longer than 1 week were consistent with the main analyses. Meta-regression analysis demonstrated that practical course significantly increased estimate effect for knowledge score (P = .002) and skills score (P = .0001). Conclusions Meta-analysis of best available evidence (level 1a) indicates that AI-based teaching significantly improves student’s knowledge， P  .00001)， 0.24–0.49， MEDLINE。

and teaching satisfaction score via fixed-effect modelling. Results Fourteen RCTs enrolling 1116 students who received AI-based teaching (n = 558) or traditional-based teaching (n = 558) were included. The use of AI-based teaching was associated with significantly higher knowledge score (standardized mean difference (SMD): 0.36， To evaluate comparative outcomes of artificial Intelligence (AI)-based and traditional-based teaching in medical education. Methods The literature search was carried out in CENTRAL， 95% CI，。