Predictive process monitoring aims to produce early warnings of unwanted events. We consider the use of the machine learning method extreme gradient boosting as the forecasting model in predictive monitoring. A tuning algorithm is proposed as the signaling method to produce a required false alarm rate. We demonstrate the procedure using a unique data set on mental health in the Netherlands. The goal of this application is to support healthcare workers in identifying the risk of a mental health crisis in people diagnosed with schizophrenia. The procedure we outline offers promising results and a novel approach to predictive monitoring.

中文翻译：

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使用机器学习算法进行预测监测和精神分裂症的真实例子

预测性过程监控旨在对不需要的事件产生早期预警。我们考虑使用机器学习方法极端梯度提升作为预测监测中的预测模型。提出了一种调整算法作为产生所需误报率的信令方法。我们使用荷兰独特的心理健康数据集来演示该程序。此应用程序的目标是支持医护人员识别被诊断患有精神分裂症的人出现心理健康危机的风险。我们概述的程序提供了有希望的结果和预测监测的新方法。