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
王凡立 1徐元恺 2张丽红 1杨艳丽1
作者信息
- 1. 050030 石家庄,河北医科大学第一医院肾内科
- 2. 310030 杭州,浙江医院肾内科
- 折叠
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 fistu-la,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.
Abstract
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Key words
Arteriovenous fistula/Artificial intelligence/Machine learning/Audio引用本文复制引用
基金项目
河北省卫生健康创新专项(22377794D)
出版年
2024
NETL
NSTL
万方数据