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

doi:10.5492/wjccm.v11.i5.311

Data science in the intensive care unit

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

Authors

Ming-Hao Luo¹, Dan-Lei Huang¹, Jing-Chao Luo², Ying Su², Jia-Kun Li², Guo-Wei Tu², Zhe Luo³

Affiliations

¹ Shanghai Medical College, Fudan University, Shanghai 200032, China.
² Department of Critical Care Medicine, Zhongshan Hospital, Fudan University, Shanghai 200032, China.
³ Department of Critical Care Medicine, Zhongshan Hospital, Fudan University, Shanghai 200032, China. luo.zhe@zs-hospital.sh.cn.

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.

Keywords: Artificial intelligence; COVID-19; Data science; Intensive care units; Interaction.

Publication types

Editorial