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Updated: Jun 9, 2025

Methodology for Establishing a Community-Wide Life Laboratory for Capturing Unobtrusive and Continuous Remote Activity and Health Data
Published on: July 27, 2018
Process mining in mHealth data analysis
Michael Winter1,2, Berthold Langguth3, Winfried Schlee3,4
1Institute of Clinical Epidemiology and Biometry, University of Würzburg, Würzburg, Germany. michael.winter@uni-wuerzburg.de.
Abstract:
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.
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