Process mining in mHealth data analysis

IF 12.4 1区医学 Q1 HEALTH CARE SCIENCES & SERVICES

NPJ Digital Medicine Pub Date : 2024-10-23 DOI:10.1038/s41746-024-01297-0

Michael Winter, Berthold Langguth, Winfried Schlee, Rüdiger Pryss

引用次数: 0

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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移动医疗数据分析中的流程挖掘

这篇透视文章探讨了流程挖掘如何从移动医疗数据中提取临床见解，并对机器学习等数据驱动型技术进行补充。尽管技术在不断进步，但选择偏差和健康数据的复杂动态性等挑战仍需要先进的方法来应对。流程挖掘侧重于分析时间流程模式，并对健康状况的变化提供补充性见解。文章强调了流程挖掘在分析移动医疗数据及其他方面的潜力。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

NPJ Digital Medicine Multiple-

CiteScore

25.10

自引率

3.30%

发文量

170

审稿时长

15 weeks

期刊介绍： npj Digital Medicine is an online open-access journal that focuses on publishing peer-reviewed research in the field of digital medicine. The journal covers various aspects of digital medicine, including the application and implementation of digital and mobile technologies in clinical settings, virtual healthcare, and the use of artificial intelligence and informatics. The primary goal of the journal is to support innovation and the advancement of healthcare through the integration of new digital and mobile technologies. When determining if a manuscript is suitable for publication, the journal considers four important criteria: novelty, clinical relevance, scientific rigor, and digital innovation.