基于人工智能及音频技术监测动静脉内瘘的研究进展  

Research progress in the monitoring of arteriovenous fistula based on artificial intelligence and audio technology

作　　者：王凡立 徐元恺[2] 张丽红[1] 杨艳丽 WANG Fan-li;XU Yuan-kai;ZHANG Li-hong;YANG Yan-li(Department of Nephrology,The First Hospital of Hebei Medical University,Shijiazhuang 050030,China;Department of Nephrology,Zhejiang Hospital,Hangzhou 310030,China)

机构地区：[1]河北医科大学第一医院肾内科,石家庄050030 [2]浙江医院肾内科,杭州310030

出　　处：《中国血液净化》2024年第2期125-129,共5页Chinese Journal of Blood Purification

基　　金：河北省卫生健康创新专项(22377794D)。

摘　　要：血液透析是终末期肾病主要的肾脏替代治疗方式,自体动静脉内瘘(arteriovenous fistula,AVF)是各大指南推荐的首选血管通路。但反复的AVF失功不仅影响患者生存质量,亦增加巨大的经济、社会负担。因此对AVF功能及时评估并适时给予干预措施至关重要。而相较于物理检查,人工智能因其可以实现检查结果的精确量化、诊疗同质化及远程诊疗而成为研究热点。本文主要对AVF声学特征、声学特征提取方法以及机器学习方法的选择、AVF人工智能监测系统的开发3个方面的研究进展做综述,以期梳理研究脉络,探索临床研究方向。Hemodialysis is the mainstay of renal replacement therapy for end-stage renal disease,and ar-teriovenous fistula(AVF)is the preferable method for vascular access recommended by major guidelines.However,repeated AVF failures affect the quality of life of the patients,and increase economic and social bur-dens.Therefore,continuous assessment of AVF function and early intervention to abnormal AVF is essential.Currently,artificial intelligence has become a hot issue due to the advantages of accurate and quantified re-sults,homogenized and remote diagnosis and treatment,as compared to the physical examination of AVF.In this article,research progresses in AVF acoustic feature and its extraction method,selection of machine learn-ing method,and the development of AVF monitoring system by artificial intelligence are reviewed in order to explore the research pathways and the direction of clinical research.

关 键 词：AVF 人工智能 机器学习 音频 

分 类 号：R318.16[医药卫生—生物医学工程]