Data science in the intensive care unit.

Ming-Hao Luo, Dan-Lei Huang, Jing-Chao Luo, Ying Su, Jia-Kun Li, Guo-Wei Tu, Zhe Luo
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引用次数: 1

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.

Abstract Image

Abstract Image

重症监护病房的数据科学。
在这篇社论中,我们评论了当前重症监护病房(icu)数据科学的发展和部署。icu中的数据可以分为定性和定量数据,需要不同的翻译和解释技术。数据科学,以人工智能(AI)的形式,应该找到医生,数据和算法之间的正确互动。对于个体患者和医生来说,败血症和机械通气是人工智能被广泛研究的两个重要方面。然而,主要的偏倚风险、缺乏通用性和较差的临床价值仍然存在。应更加重视AI在icu中的部署,促进AI发展。对于ICU管理而言,人工智能在改变资源配置方面具有巨大潜力。2019年冠状病毒病大流行为建立这种系统提供了机会,应该进一步研究。在设计这样的人工智能时,必须解决伦理问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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