慢阻肺数字疗法探讨  

Discussion on digital therapy of chronic obstructive pulmonary disease

作　　者：卢赛虎 张浩 牟岫影 王鹏 杜利东 陈贤祥 黄可[4] 杨汀[4] 方震 LU Saihu;ZHANG Hao;MOU Xiuying;WANG Peng;DU Lidong;CHEN Xianxiang;HUANG Ke;YANG Ting;FANG Zhen(Aerospace Information Research Institute,Chinese Academy of Sciences,Beijing 100190,China;School of Electronic,Electrical and Communication Engineering,University of Chinese Academy of Sciences,Beijing 100049;Research Unit of Personalized Management of Chronic Respiratory Disease,Chinese Academy of Medical Sciences,Beijing 100190;China-Japan Friendship Hospital,Beijing 100029)

机构地区：[1]中国科学院空天信息创新研究院,北京100190 [2]中国科学院大学电子电气与通信工程学院,北京100049 [3]中国医学科学院个性化呼吸慢病管理创新单元,北京100190 [4]中日友好医院,北京100029

出　　处：《生物医学工程研究》2023年第3期279-284,共6页Journal Of Biomedical Engineering Research

基　　金：国家重点研发计划项目(2020YFC2003703);中国医学科学院医学与健康科技创新工程项目资助(2019-I2M-5-019)。

摘　　要：慢性阻塞性肺疾病(chronic obstructive pulmonary disease,COPD)是一种以持续性气流受限为主要特征的常见慢性呼吸疾病,近年来给社会带来严重负担。数字疗法是一种新兴的医学治疗方法,利用获取的疾病大数据,结合人工智能技术,可有效提高疾病的治疗效果。本文简述了数字疗法在COPD预防、管理以及治疗中的应用研究进展,包括数据获取、分析及管理,并对比分析了常规疗法与数字疗法在COPD诊疗过程中的优缺点,总结了数字疗法在COPD预防、管理及治疗过程中的有效性,并对其发展前景进行了展望。Chronic obstructive pulmonary disease(COPD)is a common chronic respiratory disease characterized by persistent airflow limitation,which has brought serious burden to the society in recent years.Digital therapy is an emerging medical treatment method,which can effectively improve the treatment effect of diseases by using the obtained big data of diseases,combined with artificial intelligence technology.This paper briefly describes the application research progress of digital therapy in the prevention,management and treatment of COPD,including data acquisition,analysis and management,compares and analyzes the advantages and disadvantages of conventional therapy and digital therapy in the diagnosis and treatment of COPD,summarizes the effectiveness of digital therapy in the prevention,management and treatment of COPD,and prospects its development.

关 键 词：慢阻肺 数字健康 症状监测 人工智能 慢病管理 

分 类 号：R318[医药卫生—生物医学工程] R563[医药卫生—基础医学] TP18[自动化与计算机技术—控制理论与控制工程]