PDF(Pubmed)
Abstract：
BACKGROUND: Major bile duct injuries during laparoscopic cholecystectomy (LC), often stemming from errors in surgical judgment and visual misperception of critical anatomy, significantly impact morbidity, mortality, disability, and health care costs.
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.
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.
摘要：
背景：腹腔镜胆囊切除术（LC）中的主要胆管损伤，通常源于手术判断的错误和对关键解剖结构的视觉误解，显着影响发病率，死亡率,残疾,和医疗费用。
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。
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。
