数据共享
数据管理
多样性(控制论)
数据质量
计算机科学
数据科学
最佳实践
数据集成
集合(抽象数据类型)
医学
数据挖掘
工程类
替代医学
人工智能
程序设计语言
管理
公制(单位)
经济
病理
运营管理
作者
Matthias Ganzinger,Enrico Glaab,Jules N. A. Kerssemakers,Sven Nahnsen,Ulrich Sax,Nadine S. Schaadt,Matthieu-P. Schapranow,Thorsten Tiede
出处
期刊:Elsevier eBooks
[Elsevier]
日期:2021-01-01
卷期号:: 532-543
被引量:2
标识
DOI:10.1016/b978-0-12-801238-3.11621-6
摘要
Systems medicine is an interdisciplinary approach in medicine that relies on computational models based on data from a variety of sources. Typically, such sources include clinical and biomedical data with heterogeneous data definitions that are sometimes not even structured in a useful way. Consequently, the systematic management of data is an important element for the successful implementation of systems medicine in both research and clinical application. In this article, we provide an overview over the following selected aspects of data management: Integration of multiple data sources IT infrastructures Data protection regulations Data history and data quality Data sharing/FAIR principles Use and access policies The presented best practices and experiences result from several systems medicine projects in which the authors have participated. They can be considered as recommendations for future projects in order to quickly set up data management infrastructures for systems medicine.
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