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重症监护病房中的数据科学。

Data science in the intensive care unit.

作者信息

Luo Ming-Hao, Huang Dan-Lei, Luo Jing-Chao, Su Ying, Li Jia-Kun, Tu Guo-Wei, Luo Zhe

机构信息

Shanghai Medical College, Fudan University, Shanghai 200032, China.

Department of Critical Care Medicine, Zhongshan Hospital, Fudan University, Shanghai 200032, China.

出版信息

World J Crit Care Med. 2022 Sep 9;11(5):311-316. doi: 10.5492/wjccm.v11.i5.311.

Abstract

In this editorial, we comment on the current development and deployment of data science in intensive care units (ICUs). Data in ICUs can be classified into qualitative and quantitative data with different technologies needed to translate and interpret them. Data science, in the form of artificial intelligence (AI), should find the right interaction between physicians, data and algorithm. For individual patients and physicians, sepsis and mechanical ventilation have been two important aspects where AI has been extensively studied. However, major risks of bias, lack of generalizability and poor clinical values remain. AI deployment in the ICUs should be emphasized more to facilitate AI development. For ICU management, AI has a huge potential in transforming resource allocation. The coronavirus disease 2019 pandemic has given opportunities to establish such systems which should be investigated further. Ethical concerns must be addressed when designing such AI.

摘要

在这篇社论中,我们对重症监护病房(ICU)中数据科学的当前发展和应用进行评论。ICU中的数据可分为定性和定量数据,需要不同的技术来转换和解释这些数据。以人工智能(AI)形式存在的数据科学应找到医生、数据和算法之间的正确交互方式。对于个体患者和医生而言,脓毒症和机械通气一直是人工智能得到广泛研究的两个重要方面。然而,偏差、缺乏普遍性和临床价值不佳等主要风险依然存在。应更加强调在ICU中部署人工智能以促进其发展。对于ICU管理而言,人工智能在改变资源分配方面具有巨大潜力。2019冠状病毒病大流行提供了建立此类系统的机会,对此应进一步研究。在设计此类人工智能时,必须解决伦理问题。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3275/9483002/b995653013e9/WJCCM-11-311-g001.jpg

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