Open AccessData science in the intensive care unit
Author(s) -
Minghao Luo,
Daixin Huang,
Jing-Chao Luo,
Ying Su,
Jia-Kun Li,
Guo-wei Tu,
Zhe Luo
Publication year - 2022
Publication title -
world journal of critical care medicine
Language(s) - English
Resource type - Journals
ISSN - 2220-3141
DOI - 10.5492/wjccm.v11.i5.311
Subject(s) - generalizability theory , software deployment , intensive care unit , intensive care , pandemic , covid-19 , intensive care medicine , medicine , data science , computer science , artificial intelligence , disease , psychology , infectious disease (medical specialty) , pathology , developmental psychology , operating system
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.