医学新知2024,Vol.34Issue(4) :473-480.DOI:10.12173/j.issn.1004-5511.202311039

人工智能在慢加急性肝衰竭预后评估中的应用研究进展

Progress of the artificial intelligence application in prognosis assessment of acute-on-chronic liver failure

龚红梅 毛青 蒋黎
医学新知2024,Vol.34Issue(4) :473-480.DOI:10.12173/j.issn.1004-5511.202311039

人工智能在慢加急性肝衰竭预后评估中的应用研究进展

Progress of the artificial intelligence application in prognosis assessment of acute-on-chronic liver failure

龚红梅 1毛青 1蒋黎1
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作者信息

  • 1. 陆军军医大学第一附属医院感染病科(重庆 400038)
  • 折叠

摘要

随着人工智能(artificial intelligence,AI)技术在医疗保健、疾病诊断、治疗、预防中的快速发展,AI在肝脏疾病中的应用也越来越受到人们的关注.慢加急性肝衰竭(acute-on-chronic liver failure,ACLF)是一种多种诱因所致的以慢性肝病急性肝功能恶化为表现的综合征,伴有器官衰竭,短期病死率高.早期发现、准确评估预后并及早干预对改善ACLF患者的疾病转归至关重要.尽管关于ACLF预后相关因素及国内外常用预后评分模型的研究一直是肝病领域的关注热点,但AI在ACLF的预后预测中的临床价值却鲜有报道.本文将着重阐述AI在ACLF预后预测评估中的应用,旨在帮助临床医生了解最新模型的框架,为ACLF疾病预后预测模型提供新思路.

Abstract

With the rapid development of artificial intelligence(AI)technology in healthcare,disease diagnosis,and treatment and prevention,the application of AI in liver diseases is gaining increasely attention as well.Acute-on-chronic liver failure(ACLF)is a multifactorial syndrome characterized by acute decompensated liver deterioration of chronic liver disease,accompanied by organ failure(not only liver failure or extra-hepatic organ failure),with a high short-term mortality rate.Early detection,accurate assessment of prognosis and early intervention are essential to improve the clinical outcome of ACLF patients.Although studies on prognostic factors of ACLF and common prognostic scoring models at home and abroad have been the focus of attention in the field of liver disease,the clinical value of AI in the diagnosis and prognosis prediction of ACLF has rarely been reported.This paper focuses on the application of AI in the prognosis prediction and evaluation of ACLF,aiming to help clinicians understand the framework of the latest model and provide new ideas for the prognosis prediction model of ACLF.

关键词

人工智能/慢加急性肝衰竭/预后/评估模型

Key words

Artificial intelligence/Acute-on-chronic liver failure/Prognosis/Evaluation model

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基金项目

国家科技重大专项(2017ZX10203201006)

重庆市英才计划(CQYC201903063)

出版年

2024
医学新知
武汉大学中南医院,中国农工民主党湖北省委医药卫生工作委员会

医学新知

CSTPCD
影响因子:0.243
ISSN:1004-5511
参考文献量28
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