机器学习在急诊医疗服务体系中的应用现状与展望  

Application and outlook of machine learning in emergency medical service system

作　　者：李萍[1] 聂虎(审校)[1] LI Ping;NIE Hu

机构地区：[1]四川大学华西医院急诊科,成都610041

出　　处：《临床急诊杂志》2020年第6期507-511,共5页Journal of Clinical Emergency

基　　金：四川大学华西医院新型冠状病毒科技攻关项目(No:HX2019nCoV026)。

摘　　要：机器学习(machine learning,ML)是计算机通过模拟人类学习行为并获取处理数据的方法。ML作为人工智能(artificial intelligence,AI)的一个分支[1],以精确快速处理大量数据为特点,目前已经应用到医学的很多领域,如医学影像、实验室检查、流行病学以及疾病的预测、识别与管理等。ML与传统统计方法相比,前者在处理大量复杂的数据,比如海量的医疗数据方面,表现出更佳的处理能力[2]。Machine learning(ML),as a method of realizing artificial intelligence,has been applied in many fields of Medicine as a result of its powerful data processing capability,which increases the ability to process the huge medical data and the work efficiency of the medical staff.Overload running in emergency department,a common problem in many hospitals,as well as the severity and rapid change of the patients’condition necessitate the assist of ML to improve the imbalance between the number of the medical staff and the patients,to enhance the capacity of doctor to detect and manage critically ill patients.In this article,we will review the application of ML in different scenarios such as pre-hospital and in-hospital emergency care and critical care in the emergency medical service system.

关 键 词：机器学习 急诊医疗服务体系 院前急救 院内急诊 危重症监护 

分 类 号：R459.7[医药卫生—急诊医学]