斯坦福医学加速临床数据科学的新范式
A new paradigm for accelerating clinical data science at Stanford Medicine
摘要：
斯坦福医学正在为我们的学术研究社区建立一个新的数据平台，以更好地进行临床数据科学。医院拥有大量患者数据，研究人员已经证明有能力重复使用这些数据和人工智能方法来获得新的见解、支持患者护理并提高护理质量。然而，目前使用的传统数据仓库和诚实代理方法是不可伸缩的。我们正在建立一个新的安全大数据平台，旨在缩短访问和分析数据的时间。在该平台中，数据是匿名的，以保护患者数据隐私，并在机构审查委员会（IRB）提交前提供。此外，数据是标准化的，这样在斯坦福大学完成的分析可以在其他地方使用相同的分析代码和临床概念进行复制。最后，分析数据仓库与安全的数据科学计算设施集成以支持大规模数据分析。该生态系统旨在将现代数据科学社区带到安全和协作的大数据分析环境中高度敏感的临床数据，目标是实现更大，更好，更快的科学。
英文摘要：
Stanford Medicine is building a new data platform for our academic research community to do better clinical data science. Hospitals have a large amount of patient data and researchers have demonstrated the ability to reuse that data and AI approaches to derive novel insights, support patient care, and improve care quality. However, the traditional data warehouse and Honest Broker approaches that are in current use, are not scalable. We are establishing a new secure Big Data platform that aims to reduce time to access and analyze data. In this platform, data is anonymized to preserve patient data privacy and made available preparatory to Institutional Review Board (IRB) submission. Furthermore, the data is standardized such that analysis done at Stanford can be replicated elsewhere using the same analytical code and clinical concepts. Finally, the analytics data warehouse integrates with a secure data science computational facility to support large scale data analytics. The ecosystem is designed to bring the modern data science community to highly sensitive clinical data in a secure and collaborative big data analytics environment with a goal to enable bigger, better and faster science.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
