标题： 评估外部因素对突发事件发生的影响 显示英文标题

标题： Assessing the impact of external factors on the occurrence of emergencies

摘要： 本研究利用由Centre Hospitalier Universitaire Vaudois (CHUV) 调度中心提供的历史数据，调查了与天气、道路交通状况、空气质量及时间相关的19个外部因素对紧急事件发生的影响。 该中心负责管理瑞士法语区大部分地区的紧急医疗服务（EMS）资源。 首先，采用经典的统计方法，如相关性、卡方检验、学生氏$t$-检验和信息值，以确定紧急事件的发生与所考虑参数之间的依赖关系。 此外，使用极端梯度提升（XGBoost）和多层感知器（MLP）模型计算SHapley Additive exPlanations（SHAP）值和排列重要性。 结果表明，一天中的小时数以及相关参数在紧急事件的发生中起着关键作用。 相反，其他因素对紧急事件的发生没有显著影响。 随后，将仅考虑一天中小时数的简化模型与我们的XGBoost和MLP模型进行比较。 这些比较显示，在性能方面，这三个模型之间没有显著差异，支持在此情境下使用基本模型。 这些观察结果为EMS资源重新部署策略提供了有价值的见解，有助于预测建模工作，并为EMS背景下的决策提供依据。 其意义在于提高EMS质量，使本研究变得至关重要。 显示英文摘要

摘要： This study investigates the impact of 19 external factors, related to weather, road traffic conditions, air quality, and time, on the occurrence of emergencies using historical data provided by the dispatch center of the Centre Hospitalier Universitaire Vaudois (CHUV). This center is responsible for managing Emergency Medical Service (EMS) resources in the majority of the French-speaking part of Switzerland. First, classical statistical methods, such as correlation, Chi-squared test, Student's $t$-test, and information value, are employed to identify dependencies between the occurrence of emergencies and the considered parameters. Additionally, SHapley Additive exPlanations (SHAP) values and permutation importance are computed using eXtreme Gradient Boosting (XGBoost) and Multilayer Perceptron (MLP) models. The results indicate that the hour of the day, along with correlated parameters, plays a crucial role in the occurrence of emergencies. Conversely, other factors do not significantly influence emergency occurrences. Subsequently, a simplified model that considers only the hour of the day is compared with our XGBoost and MLP models. These comparisons reveal no significant difference between the three models in terms of performance, supporting the use of the basic model in this context. These observations provide valuable insights for EMS resource relocation strategies, benefit predictive modeling efforts, and inform decision-making in the context of EMS. The implications extend to enhancing EMS quality, making this research essential.