中国血液净化

中国血液净化 ›› 2025, Vol. 24 ›› Issue (05): 402-405.doi: 10.3969/j.issn.1671-4091.2025.05.009

• 综述 • 上一篇    

人工智能在血液透析并发症预测与患者管理中的研究进展

宋明阳   侯佐贤   王 颖   陈丽萌   

  1. 100730 北京，1中国医学科学院 北京协和医学院 北京协和医院肾内科 疑难重症及罕见病全国重点 实验室（北京协和医院）

  • 收稿日期:2024-12-10 修回日期:2025-01-06 出版日期:2025-05-12 发布日期:2025-05-12
  • 通讯作者: 陈丽萌 E-mail:chenlimeng@pumch.cn
  • 基金资助:
    新一代人工智能国家科技重大专项(2022ZD0116003)

Research progresses in artificial intelligence for hemodialysis complication prediction and patient management

ONG Ming-yang, HOU Zuo-xian, WANG Ying, CHEN Li-meng   

  1. Department of Nephrology, State Key Laboratoty of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing 100730, China
  • Received:2024-12-10 Revised:2025-01-06 Online:2025-05-12 Published:2025-05-12
  • Contact: 100730 北京，1中国医学科学院 北京协和医学院 北京协和医院肾内科 疑难重症及罕见病全国重点实验室（北京协和医院） E-mail:chenlimeng@pumch.cn

摘要： 血液透析是治疗终末期肾病的关键方法之一，但存在患者死亡率高，透析相关并发症多，慢病管理需求高等问题尚待解决。这一现状揭示了强化血液透析并发症风险预测、精准诊断及患者全面管理与支持的迫切需求。人工智能技术的迅猛发展与在血液透析领域的逐步融合，正展现出对于解决该领域存在问题的重要潜力。本文旨在概述人工智能在血液透析并发症预测与诊断方面的应用现状，并基于现有成果与趋势，阐述其在患者管理方面的未来发展方向。

关键词: 人工智能, 血液透析, 透析中低血压, 动静脉内瘘, 大语言模型

Abstract: Hemodialysis is one of the crucial treatments for end stage renal disease. However, there are still issues to be solved, such as higher mortality, various dialysis-related complications and increased demands for chronic disease management. These situations highlight urgent necessities to enhance risk prediction,  precise diagnosis of complication, and comprehensive management of the patients. The rapid development of artificial intelligence and its gradual integration into hemodialysis have provided great potentials to address the existing issues. This review aims to outline the current application status of artificial intelligence in prediction and diagnosis of hemodialysis complications and to elaborate its development directions in patient management based on existed achievements and trends.

Key words: Artificial intelligence, Hemodialysis, Intradialytic hypotension, Arteriovenous fistula, Large language model

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