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Review
. 2021 May 13:8:665464.
doi: 10.3389/fmed.2021.665464. eCollection 2021.

Artificial Intelligence for Clinical Decision Support in Sepsis

Miao Wu  1 , Xianjin Du  2 , Raymond Gu  3 , Jie Wei  1
Affiliations
Review

Artificial Intelligence for Clinical Decision Support in Sepsis

Miao Wu et al. Front Med (Lausanne). .

Abstract

Sepsis is one of the main causes of death in critically ill patients. Despite the continuous development of medical technology in recent years, its morbidity and mortality are still high. This is mainly related to the delay in starting treatment and non-adherence of clinical guidelines. Artificial intelligence (AI) is an evolving field in medicine, which has been used to develop a variety of innovative Clinical Decision Support Systems. It has shown great potential in predicting the clinical condition of patients and assisting in clinical decision-making. AI-derived algorithms can be applied to multiple stages of sepsis, such as early prediction, prognosis assessment, mortality prediction, and optimal management. This review describes the latest literature on AI for clinical decision support in sepsis, and outlines the application of AI in the prediction, diagnosis, subphenotyping, prognosis assessment, and clinical management of sepsis. In addition, we discussed the challenges of implementing and accepting this non-traditional methodology for clinical purposes.

Keywords: artificial intelligence; deep learning; early prediction; machine learning; sepsis.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Roadmap for machine learning systems.
Figure 2
Figure 2
Two methods of machine learning. (A) Supervised learning. (B) Unsupervised learning.
See this image and copyright information in PMC

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