This perspective article explores how process mining can extract clinical insights from mobile health data and complement data-driven techniques like machine learning. Despite technological advances, challenges such as selection bias and the complex dynamics of health data require advanced approaches. Process mining focuses on analyzing temporal process patterns and provides complementary insights into health condition variability. The article highlights the potential of process mining for analyzing mHealth data and beyond.

中文翻译：

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mHealth 数据分析中的流程挖掘

这篇观点文章探讨了流程挖掘如何从移动健康数据中提取临床洞察，并补充机器学习等数据驱动技术。尽管技术取得了进步，但选择偏差和健康数据的复杂动态等挑战需要先进的方法。流程挖掘侧重于分析时间流程模式，并提供对健康状况变化的补充见解。本文重点介绍了流程挖掘在分析 mHealth 数据等方面的潜力。