发表机构
University of Trento; UiT the Arctic University of Norway（特伦托大学; 挪威北极大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
针对现有外科AI忽略团队互动建模的问题，提出tempo-relational框架结合Time-Expanded图，通过反事实程序生成可解释建议，在模拟手术实验中提升了多目标预测性能。
AI 中文摘要
在外科手术中，患者安全不仅受到技术问题的威胁，还受到团队协作不佳的影响。然而，现有的基于AI的外科解决方案主要关注视觉工作流程和技术执行，忽略了对团队互动的建模，错失了主动支持临床医生提升团队协作技能的机会。为解决这一差距，我们提出了一种tempo-relational框架，用于从多模态观察中建模手术团队动态。通过利用Time-Expanded图，该方法既能捕捉关系结构和时间演变，又具有强表达性，同时在外科环境典型的低数据 regime 中保持稳健性。除预测外，此类建模还能为临床医生生成高效、可解释且可行动的建议。更具体地说，我们通过反事实程序生成建议，该程序识别与团队绩效提升相关的个体行为和互动模式的最小且结构化的变化。对模拟外科手术的实验表明，我们的方法在不同的行为和互动目标中提高了预测性能，同时为团队动态提供了有意义的见解。这项工作将外科AI从基于结果的预测推进到以社会为基础、以团队为中心且可行动的范式，以更好地理解和支持外科环境中团队技能的发展。
英文摘要
In surgery, patient safety is threatened not only by technical issues but also by poor teamwork. However, existing surgical AI-based solutions focus mainly on visual workflow and technical execution, neglecting the modeling of team interactions and missing opportunities to actively support clinicians in improving their teamwork skills. To address this gap, we propose a tempo-relational framework for modeling surgical team dynamics from multimodal observations. By leveraging Time-Expanded graphs, the approach captures both relational structure and temporal evolution, achieving strong expressivity while remaining robust in the low-data regime typical of surgical settings. Beyond prediction, such modeling enables the generation of efficient, interpretable, and actionable suggestions for clinicians. More specifically, we generate suggestions via a counterfactual procedure that identifies minimal yet structured changes in individual behaviors and interaction patterns associated with improvements in team performance. Experiments with simulated surgical procedures show that our approach improves predictive performance in diverse behavioral and interaction goals while offering meaningful insights into team dynamics. This work advances surgical AI beyond outcome-driven prediction towards a socially grounded, team-centric, and actionable paradigm to better understand and support the development of team skills in surgical settings.
CommentsAccepted at ACM Multimedia 2026
