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摘要翻译：
R包“RICU”为处理不同的重症监护室(ICU)数据集提供计算基础设施，能够编写与数据集无关的分析代码，从而促进多中心训练和机器学习模型的验证。该软件包的设计强调了对新数据集和临床数据概念的可扩展性，目前支持加载大约100个患者变量，这些变量对应于来自欧洲和美国收集的4个数据源的总共319,402例ICU入院病例。通过允许添加用户指定的医学概念和数据源，“RICU”的目的是促进稳健的、基于数据的重症监护研究，允许用户相对容易地从外部验证他们的方法或结论，进而促进该领域的可复制和透明的工作。
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英文标题：
《ricu: R's Interface to Intensive Care Data》
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作者：
Nicolas Bennett, Drago Ple\v{c}ko, Ida-Fong Ukor, Nicolai Meinshausen,
Peter B\"uhlmann
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最新提交年份：
2021
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分类信息：
一级分类：Statistics 统计学
二级分类：Applications 应用程序
分类描述：Biology, Education, Epidemiology, Engineering, Environmental Sciences, Medical, Physical Sciences, Quality Control, Social Sciences
生物学，教育学，流行病学，工程学，环境科学，医学，物理科学，质量控制，社会科学
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一级分类：Quantitative Biology 数量生物学
二级分类：Other Quantitative Biology 其他定量生物学
分类描述：Work in quantitative biology that does not fit into the other q-bio classifications
不适合其他q-bio分类的定量生物学工作
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英文摘要：
Providing computational infrastructure for handling diverse intensive care unit (ICU) datasets, the R package 'ricu' enables writing dataset-agnostic analysis code, thereby facilitating multi-center training and validation of machine learning models. The package is designed with an emphasis on extensibility both to new datasets as well as clinical data concepts, and currently supports the loading of around 100 patient variables corresponding to a total of 319,402 ICU admissions from 4 data sources collected in Europe and the United States. By allowing for the addition of user-specified medical concepts and data sources the aim of 'ricu' is to foster robust, data-based intensive care research, allowing the user to externally validate their method or conclusion with relative ease, and in turn facilitating reproducible and therefore transparent work in this field.
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PDF链接：
https://arxiv.org/pdf/2108.00796
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