中国血液净化

中国血液净化 ›› 2022, Vol. 21 ›› Issue (08): 599-602.doi: 10.3969/j.issn.1671-4091.2022.08.014

• 综述 • 上一篇    下一篇

基于人工智能的急性肾损伤预警系统研究进展

赵 丹   余 晨   张颖莹   

  1. 200065 上海，同济大学附属同济医院肾内科 
  • 收稿日期:2022-02-03 修回日期:2022-03-23 出版日期:2022-08-12 发布日期:2022-08-12
  • 通讯作者: 张颖莹 E-mail:idklaa@126.com
  • 基金资助:
    国家自然基金面上项目(82170696)； 国家自然基金青年项目(81900622)； 中关村肾病血液净化创新联盟
     CKD-MBD青年研究项目(NBPIA20QC0101)； 上海市同济医院专病数据库[TJ(DB)2103]； 上海市同济医院
    临床培育项目[ITJ(QN)2104]； 新兴前沿技术联合攻关项目(SHDC12022104)

Advances in early warning system for acute kidney injury based on artificial intelligence 

ZHAO Dan, YU chen, ZHANG Ying-ying   

  1. University, Shanghai 200065, China
  • Received:2022-02-03 Revised:2022-03-23 Online:2022-08-12 Published:2022-08-12
  • Contact: ZHANG Ying-ying E-mail:idklaa@126.com

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摘要： 急性肾损伤(acute kidney injury，AKI)是由多种病因导致的肾功能短期内急剧下降，具有发病率高、致死率高、临床预后差等特点。对于AKI患者早期识别、早期诊断并适时给予干预措施是改善患者不良预后的关键。随着人工智能的普及，AKI预警系统经历了从基于简单算法的电子警报到多特征学习预测模型的逐步发展，能够利用多维复杂的临床数据主动识别高危人群，提醒临床医生早期干预以改善患者不良预后。本文就人工智能在AKI预警系统中的研究进展进行综述。

关键词: 急性肾损伤；预测模型；电子警报；机器学习 ,  ,  ,  

Abstract: Acute kidney injury (AKI) is a common complication in hospitalized patients, and is associated with poor outcomes and higher mortality. Early identifying AKI before function loss is crucial to reverse the injury. Therefore, establishing an early-warning system for AKI is essential for clinicians to make the diagnosis and treatment decisions earlier. With the development of artificial intelligence, a variety of electronic alerts and machine learning-based predictive models to predict the risks of AKI have been developed. In the current review, we summarize the advances in the electronic systems based on artificial intelligence for predicting AKI. 

Key words: Acute kidney injury; , Prediction model; , E-alert; , Machine learning

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