机器学习在急诊科诊疗中的应用研究进展  

Research progress in the application of machine learning in diagnosis and treatment of diseases in department of emergency

作　　者：彭川[1] 熊辉[1] Peng Chuan;Xiong Hui(Department of Emergency,Peking University First Hospital,Beijing 100034,China)

机构地区：[1]北京大学第一医院急诊科,北京100034

出　　处：《中国中西医结合急救杂志》2022年第2期253-256,共4页Chinese Journal of Integrated Traditional and Western Medicine in Intensive and Critical Care

摘　　要：机器学习是以数据资料为基础,利用计算机构建概率统计模型,对数据进行预测与分析的前沿交叉学科。近年来,随着科技的发展,医疗数据的信息化和规范化程度不断提高,利用机器学习对体量庞大、类型多样的医疗数据进行深度挖掘和分析,探索疾病与相关参数的深层次联系,为医疗行为提供风险预警、决策支持及个性化建议,并已在医疗多领域得以实现。将机器学习应用于急诊诊疗工作中,有助于早期识别急危重症患者,及时发现潜在疾病风险,精准提供诊疗决策支持,从而提高诊疗效率和诊治水平,改善急诊拥挤问题,可在提升医疗服务质量的同时减轻急诊医务人员工作强度。本文基于国内外最新研究成果,从急诊分诊、疾病诊断与治疗决策、疾病风险预警和不良事件预测4个方面,对机器学习在急诊科诊疗工作中的应用研究进展进行综述。Machine learning is a frontier interdisciplinary subject based on data information,utilizing computers to construct probabilistic statistical models to predict and analyze data.In recent years,with the development of science and technology,the informatization and standardization of medical data has been continuously improved,the use of machine learning for deep mining and analyzing of large volumes and diverse types of medical data,exploring deep links between diseases and related parameters,providing risk warning,decision support and personalized advice for medical practices,has been realized in many areas of healthcare.The application of machine learning in diagnosis and treatment of diseases in the emergency department will play a role in the early identification of patients with acute and critical illnesses,timely detection of potential disease risks,accurate support of diagnosis and treatment decisions,so as to improve the work efficiency and treatment level,alleviate the emergency medical congestion,enhance the quality of medical services and in the mean time reduce the workload of medical staffs.This paper reviews the domestic and abroad current research progresses and achievements on the application of machine learning in diagnosis and treatment in the emergency department from four aspects:emergency triage,disease diagnosis and treatment decision,disease risk warning,and adverse event prediction.

关 键 词：机器学习 急诊科 大数据 

分 类 号：R47[医药卫生—护理学]