OBJECTIVE: To enhance safe LC learning, we developed an educational mobile game, LapBot Safe Chole, which uses an artificial intelligence (AI) model to provide real-time coaching and feedback, improving intraoperative decision-making.
METHODS: LapBot Safe Chole offers a free, accessible simulated learning experience with real-time AI feedback. Players engage with intraoperative LC scenarios (short video clips) and identify ideal dissection zones. After the response, users receive an accuracy score from a validated AI algorithm. The game consists of 5 levels of increasing difficulty based on the Parkland grading scale for cholecystitis.
RESULTS: Beta testing (n=29) showed score improvements with each round, with attendings and senior trainees achieving top scores faster than junior residents. Learning curves and progression distinguished candidates, with a significant association between user level and scores (P=.003). Players found LapBot enjoyable and educational.
CONCLUSIONS: LapBot Safe Chole effectively integrates safe LC principles into a fun, accessible, and educational game using AI-generated feedback. Initial beta testing supports the validity of the assessment scores and suggests high adoption and engagement potential among surgical trainees.
目的:为了提高LC学习的安全性,我们开发了一款教育手机游戏,LapBotSafeChole,它使用人工智能(AI)模型来提供实时指导和反馈,改善术中决策。
方法:LapBotSafeChole提供免费的,具有实时AI反馈的可访问模拟学习体验。玩家参与术中LC场景(短视频剪辑)并确定理想的解剖区域。在回应之后,用户从经过验证的AI算法中获得准确性评分。游戏包括5个级别的难度增加的基础上的Parkland等级为胆囊炎。
结果:Beta测试(n=29)显示每轮得分提高,主治医师和高级学员的得分比初级住院医师快。学习曲线和进展杰出的候选人,用户水平和分数之间存在显著关联(P=0.003)。玩家发现LapBot令人愉快和教育。
结论:LapBotSafeChole有效地将安全LC原理集成到一个有趣的,可访问,和使用AI生成的反馈的教育游戏。最初的beta测试支持评估分数的有效性,并建议手术学员具有很高的采用和参与潜力。