Renal Division, Department of Medicine, Peking University First Hospital; Peking University Institute of Nephrology, Beijing, China.
National Institute of Health Data Science at Peking University, Beijing, China.
Nephrology (Carlton). 2019 Nov;24(11):1097-1102. doi: 10.1111/nep.13636. Epub 2019 Aug 5.
Chronic kidney disease (CKD) is a major public health issue worldwide. However, the status of kidney health care needs to be strengthened globally and research evidence in nephrology is relatively limited. The unmet needs in nephrology leave ample space for imagination regarding leveraging big data and artificial intelligence (AI). Big data has potential to drive medical innovation, reduce medical costs and improve health care quality. Compared with other specialties such as cardiology, the scopes of utilizing big data in nephrology need to be enhanced. We reviewed the studies on the application of big data in nephrology, such as disease surveillance, risk prediction and clinical decision support systems (CDSS), and proposed several potential directions of utilizing big data and AI. The efforts including building a CKD surveillance system and collaborative network, implementing a real-world cohort in a cost-effective manner, strengthening the application and transformation of AI and CDSS, and stimulating the activeness of medical imaging in nephrology, could be considered. In the era of big data, a nephrologist would be stronger and smarter if he or she could get intelligent assistance from knowledge or big data-driven CDSS.
慢性肾脏病（CKD）是全球范围内的一个主要公共卫生问题。然而，全球范围内的肾脏保健服务需要加强，肾脏病学方面的研究证据相对有限。肾脏病学领域存在的未满足需求为利用大数据和人工智能（AI）提供了充分的想象空间。大数据有可能推动医学创新，降低医疗成本并提高医疗保健质量。与心脏病学等其他专业相比，肾脏病学在利用大数据方面的范围需要扩大。我们回顾了大数据在肾脏病学中的应用研究，例如疾病监测、风险预测和临床决策支持系统（CDSS），并提出了利用大数据和 AI 的几个潜在方向。可以考虑包括建立 CKD 监测系统和协作网络、以具有成本效益的方式实施真实世界队列、加强 AI 和 CDSS 的应用和转化，以及激发肾脏病学中医学成像的积极性等措施。在大数据时代，如果肾脏病学家能够从知识或大数据驱动的 CDSS 中获得智能辅助，他或她将更加强大和聪明。
