ricu:R与重症监护数据的接口
Nicolas Bennett1, Drago Plečko1, Ida-Fong Ukor2
1Seminar for Statistics, ETH Zürich, 8092 Zürich (Rämistrasse 101), Switzerland.
GigaScience
|June 15, 2023
概括
一个新的R包, ricu,统一了5个重症监护室 (ICU) 数据集,用于同时分析. 该工具通过协调数据,节省时间和提高ICU数据研究的可重复性来简化研究.
科学领域:
- 关键护理医学 关键护理医学
- 生物医学信息学 生物医学信息学
- 数据科学数据科学数据科学
背景情况:
- 分析来自多个重症监护室 (ICU) 数据库的数据是具有挑战性的,因为数据异质.
- 现有的ICU数据集往往是孤立的,每个数据集都需要单独的处理和协调工作.
- 需要一个统一的框架来促进大规模的,可重复的研究,使用各种ICU数据来源.
研究的目的:
- 开发一个统一的计算框架来分析来自五个大型,公开可用的重症监护室 (ICU) 数据集的数据.
- 创建一个R包,简化跨不同ICU数据库的数据访问,协调和分析.
- 促进数据共享和重症监护医学的合作研究.
主要方法:
- 综合了来自美国三个 (MIMIC-III,MIMIC-IV,eICU) 和欧洲两个 (AmsterdamUMCdb,HiTRUCS) ICU数据库的数据.
- 开发了对一组常见的临床概念的映射,利用观察医学结果伙伴关系 (OMOP) 词汇.
- 同步测量单位和数据类型,并实施统一的应用程序编程接口 (API) 来加载数据.
- 创建了R包,以提供处理这些协调ICU数据集的计算基础设施.
主要成果:
- 理科 R-Package可以同时分析来自五个主要ICU数据库的数据.
- 该软件包允许用户从统一的数据源中加载119个现有临床概念.
- 开发的框架标准化了数据表示,并促进了有效的数据检索和设置.
结论:
- 理科R套件是第一个允许同时分析多个公开可用的ICU数据集的工具.
- 这种统一的接口大大节省了研究人员的时间,并提高了ICU数据研究的可重复性.
- 未来的工作旨在扩大概念词典,以实现更全面的数据协调,促进整个社区的努力.
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