一种提高研究中动图数据效率的方法:使用统计软件来促进批量进口
Onyekachi S Ezeokeke1, Janelle M Fine2, Jennifer L Martin3,4
1School of Biological Sciences, University of California, San Diego, La Jolla, California.
概括
这项研究引入了一个Stata脚本,以高效地处理Philips Actiwatch动态图数据. 该自动化工具快速导入,添加和清理大型数据集,用于临床和研究分析.
科学领域:
- 医疗信息学 医疗信息学
- 生物医学工程 生物医学工程
- 数据科学数据科学数据科学
背景情况:
- 飞利浦Actiwatch设备广泛用于动图,但数据处理可能耗时.
- 设备的停产需要有效的方法来分析现有的和类似的动图数据.
- 大量的动图数据仍然未被分析,阻碍了临床和研究的进展.
研究的目的:
- 提交一个Stata"do"文件,用于自动导入,添加和清理来自Philips Actiware软件的原始动画数据.
- 提供一个可扩展和便携的解决方案,用于生成统一的动图数据集.
- 为了便于为临床和研究分析准备无错误的数据.
主要方法:
- 开发和应用一个用于数据处理的 Stata "do" 文件.
- 自动导入和添加来自Philips Actiware的原始数据文件.
- 数据的清理和统一到一个单一的,可分析的数据集.
主要成果:
- 在不到60秒的时间里,Stata"do"文件成功导入,添加和清除了189,596个数据时代.
- 来自35名危急病患者的48小时动态图档案的统一数据集被生成.
- 该过程产生了可用于立即分析的可用变量.
结论:
- 开发的Stata"do"文件提供了一种高效,便携和可扩展的方法来处理动画数据.
- 这种自动化方法可以大大减少为研究和临床使用准备动态图数据集的时间和错误.
- 该方法可以适应其他数据平台和动图设备.
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