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[Research progress on application of artificial intelligence in early diagnosis and prediction of sepsis].

In Zhonghua wei zhong bing ji jiu yi xue

Machine learning based artificial intelligence technology for big data processing has shown great potential in predicting patients' conditions and aiding clinical decisions, and has been widely used in the development of clinical decision support systems in recent years. Sepsis is a life-threatening organ dysfunction caused by host response disorder caused by infection, and its early recognition and treatment can significantly improve the prognosis of patients. At present, there are many deficiencies in the clinical application of sequential organ failure assessment (SOFA), bedside quick sequential organ failure assessment (qSOFA), national early warning score (NEWS), inflammatory indicators, and novel biomarkers for evaluating sepsis. Artificial intelligence has promoted the development of critical care medicine because of its ability to rapidly process and analyze massive data of severe patients. This paper reviews the recent application of artificial intelligence in the early diagnosis and prediction of sepsis, in order to emphasize the importance and limitations of artificial intelligence in the diagnosis and prediction of sepsis.

Wei Qimei, Xiu Guanghui

2022-Nov