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Review
. 2022 Mar 22;26(1):75.
doi: 10.1186/s13054-022-03915-3.

Artificial Intelligence in Critical Care Medicine

Joo Heung Yoon  1 , Michael R Pinsky  2 , Gilles Clermont  2
Affiliations
Review

Artificial Intelligence in Critical Care Medicine

Joo Heung Yoon et al. Crit Care. .

Abstract

This article is one of ten reviews selected from the Annual Update in Intensive Care and Emergency Medicine 2022. Other selected articles can be found online at https://www.biomedcentral.com/collections/annualupdate2022 . Further information about the Annual Update in Intensive Care and Emergency Medicine is available from https://link.springer.com/bookseries/8901 .

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Conflict of interest statement

Authors have no competing financial or non-financial interests for current work.

Figures

Fig. 1
Fig. 1
Conceptual role of artificial intelligence (AI)-driven predictive analytics on disease progression. The AI model enables timely detection or prediction of disease enabling clinicians to manage critically ill patients earlier (green line) than conventional strategy (yellow dotted line)
Fig. 2
Fig. 2
Dynamic, personal risk trajectory prior to cardiorespiratory instability (CRI). Black line represents control subjects. Orange line (5) indicates ‘persistent high’, purple line (4) indicates ‘early rise’, and green (3), blue (2), and red (1) lines indicate ‘late rise’ to CRI. Adapted from [9] with permission of the American Thoracic Society. Copyright © 2021 American Thoracic Society
See this image and copyright information in PMC

References

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