Artificial Intelligence for Clinical Decision Support in Sepsis

Overview

Journal Front Med (Lausanne)

Specialty General Medicine

Date 2021 May 31

PMID 34055839

Citations 16

Authors

Miao Wu

Xianjin Du

Raymond Gu

Jie Wei

Affiliations

Soon will be listed here.

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.

Citing Articles

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User-Oriented Requirements for Artificial Intelligence-Based Clinical Decision Support Systems in Sepsis: Protocol for a Multimethod Research Project.

Raszke P, Giebel G, Abels C, Wasem J, Adamzik M, Nowak H JMIR Res Protoc. 2025; 14:e62704.

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A scoping review on pediatric sepsis prediction technologies in healthcare.

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