机器学习在即时诊断中的应用进展  

Application progress of machine learning in point-of-care testing

作　　者：曹超羽 田苗[2] 许夏瑜 赵蓓[2] 游民黎 徐峰[1,2] Chaoyu Cao;Miao Tian;Xiayu Xu;Bei Zhao;Minli You;Feng Xu(Key Laboratory of Biomedical Information Engineering of Ministry'of Education,School of Life Science and Technology,Xi'an Jiaotong University,Xi’an 710049,China;Bioinspired Engineering and Biomechanics Center(BEBC),Xi'an Jiaotong University,Xi'an 710049,China;School of Engineering and Applied Science,The George Washington University,Washington DC 20052,USA)

机构地区：[1]西安交通大学生命科学与技术学院,生物信息工程教育部重点实验室,西安710049 [2]西安交通大学仿生工程与生物力学研究所(BEBC),西安710049 [3]乔治华盛顿大学工程和应用科学学院,美国华盛顿20052

出　　处：《中国科学：化学》2021年第12期1590-1614,共25页SCIENTIA SINICA Chimica

基　　金：国家重点研发计划(编号:2018YFC1707702);中央高校基本科研业务专项资金(编号:xzy012020033);陕西省重点科技创新团队计划项目(编号:2017KCT-22);中国博士后科学基金(编号:2019M663741)资助项目。

摘　　要：即时诊断凭借廉价、快速、方便和准确的特点已成为疾病诊断的一大趋势.机器学习方法的应用大大提高了即时诊断的数据处理能力,使即时诊断焕发新的生机.目前,随着智能手机等智能电子设备的普及,由即时诊断设备、智能电子产品和云端构成的物联网系统已经逐步成为现实.本文概述了机器学习算法的基本原理并阐述了其在即时诊断中的优势,着重介绍了机器学习在即时诊断中的应用现状,涵盖纸基即时检测、微流控检测和可穿戴设备等领域,并给出了根据即时诊断数据形式和检测目标选择机器学习算法的相关建议.未来以智能电子设备为平台并基于机器学习算法的即时诊断方法将成为新的趋势.In recent years, point-of-care testing(POCT) has attracted more and more attention because it is cheap, fast and easy-to-operate. However, detection accuracy and reliability remain challenging for POCT. Machine learning methods are powerful for data processing and analysis, which is the potential to improve the accuracy and reliability of POCT greatly. Additionally, it is also possible to bring breakthroughs in remote medicine and data sharing fields for POCT. In this review, we describe the basic principles of machine learning algorithms and explain their advantages in POCT;then introduce the applications of machine learning in POCT, including paper-based assays, microfluidic lab-onchip technologies, and wearable devices;after that, we also put forward suggestions on the selection of machine learning algorithms based on the data type and detection targets of POCT tasks;finally, we propose several directions of the future development of machine learning algorithms in POCT.

关 键 词：即时诊断 机器学习 纸基即时检测 微流控 可穿戴设备 

分 类 号：R44[医药卫生—诊断学] TP181[医药卫生—临床医学]