人工智能在血液透析监测和并发症预测中的研究进展  

Research progresses in the use of artificial intelligence for hemodialysis monitoring and complication prediction

作　　者：任之健 罗群[3] 蔡珂丹[3] REN Zhi-jian;LUO Qun;CAI Ke-dan(Health Science Center of Ningbo University,Ningbo 315000,China;Department of Nephrology,Ninghai County Hospital of Traditional Chinese Medicine,Ningbo 315015,China;Department of Nephrology,The Second Hospital of Ningbo City,Ningbo 315010,China)

机构地区：[1]宁波大学医学部,宁波315000 [2]宁海县中医医院肾内科,宁波315615 [3]宁波市第二医院肾内科,宁波315010

出　　处：《中国血液净化》2024年第4期294-297,共4页Chinese Journal of Blood Purification

基　　金：浙江省医药卫生项目(2024KY336);省市共建医学重点学科(2022-S03);宁波市卫生健康科技计划项目(2023Y89)。

摘　　要：终末期肾病的患病率逐年上升,血液透析是最常见的治疗方法。近年来,各种人工智能模型包括机器学习及深度学习模型在血液透析领域的研究日趋成熟,与普通线性模型相比,它们具有显著的优势和准确性,在运用血液透析患者数据来预测透析并发症、评估血管通路、管理液体容量和预测预后等方面进展迅速。在改进患者血液透析方案,提供个体化血液透析,防治并发症等方面具有很强的应用价值和广阔的前景。本综述总结了近年来人工智能模型在血液透析监测和并发症预测中的研究进展,希望为临床医生及护理工作者带来帮助,改善血液透析患者生存质量并延长生存期。The prevalence of end stage renal disease(ESRD)has been steadily increasing,and hemodialysis is a predominant treatment modality for these patients.Recently,a series of artificial intelligence(AI)models including machine learning and deep learning techniques have been successfully developed into the area of hemodialysis research.Compared with the conventional linear models,the AI models can accurately predict complications,evaluate vascular access,manage volume control and estimate prognosis based on the information from hemodialysis patients.AI also has powerful potentials in clinical practice to improve and individualize hemodialysis protocols and to prevent and treat complications.This review summarizes recent the research advances in AI models for monitoring hemodialysis and predicting complications,aiming to support doctors and nurses to improve the quality of life and to prolong the lives of hemodialysis patients.

关 键 词：人工智能 血液透析 机器学习 深度学习 

分 类 号：R459.5[医药卫生—治疗学]