【摘要】 脓毒症/脓毒性休克是高致死性疾病，患者表现出多器官功能障碍、休克甚至死亡的连续特征。脓毒症发病原因多样，患者病情发展迅速，临床医生对脓毒症患者早期诊断和预后判断不够准确。基于人工智能技术探究脓毒症患者的早期诊断和预后新方式，可能为推动脓毒症预后判断和精准治疗的质量提升发挥积极作用.本文将围绕人工智能机器学习算法在脓毒症早期诊断、精准治疗及预后预测模型的研究进展进行综述，以期为进一步开展脓毒症预测模型的研究与应用提供参考依据。更多还原

【Abstract】 Sepsis and septic shock are highly lethal diseases, patients with sepsis present with a continuum of multiple organ dysfunction, shock to death outcomes. The causes of sepsis are diverse, and the patient’s condition progresses rapidly and changeable. Therefore, clinicians are not accurate in the early diagnosis and prognosis of patients with sepsis. Based on artificial intelligence technology, exploring new methods for early diagnosis and prognosis of patients with sepsis may play a positive role in promoting the quality improvement of prognosis judgment and precision treatment of sepsis. This article will review the research progress of artificial intelligence machine learning algorithms in early diagnosis, precise treatment and prognosis prediction models of sepsis, in order to provide reference for further research and application of sepsis prediction models.更多还原