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.
翻译:为处理各种特护单位(ICU)的数据集提供计算基础设施,R包“riku”使得能够编写数据集——不可知分析代码,从而便利多中心培训和机器学习模式的验证,该包的设计强调新数据集和临床数据概念的可扩展性,目前支持从欧洲和美国收集的4个数据来源输入大约100个病人变量,相当于总共319 402个伊斯兰特护单位的接收量。通过允许增加用户指定的医疗概念和数据来源,“riku”的目的是促进强有力的、以数据为基础的特护研究,使用户能够相对容易地外部验证其方法或结论,从而便利该领域的可复制和透明工作。