机器学习助力检验医学发展  

Machine learning empowering laboratory medicine

作　　者：穆原[1] 陈红兵[1] Mu Yuan;Chen Hongbing(Department of Clinical Laboratory,Children＇s Hospital of Nanjing Medical University,Nanjing 210008,China)

机构地区：[1]南京医科大学附属儿童医院检验科,210008

出　　处：《中华检验医学杂志》2018年第8期627-630,共4页Chinese Journal of Laboratory Medicine

基　　金：南京医科大学科技发展基金项目（2016NJMUZD053）

摘　　要：医疗数据结构混杂、特征高维,传统数据仓储策略已难以满足大数据分析需求.以数据中产生模型的算法为主要研究内容的机器学习,迅即成为计算机模拟人类学习过程中智能数据分析技术的创新源泉.本文对机器学习的发展及其现处的医疗大数据背景作以简介,着重介绍其在检验医学图像识别、报告自动审核、中文医学语言处理及计算机辅助诊断中的应用,并思考其对检验医学发展带来的机遇与挑战.Traditional data storage strategy has not capacity to meet analytical needs of medical big data possessing with mixed structure and high-dimensional features. Machine learning based on algorithms that generate models in the data is becoming an innovative source of intelligent data analysis technology in computer simulation of human learning. This paper gives an introduction to the development of machine learning and its current background of medical big data. Emphases are placed on applications of machine learning in the medical image recognition, automated validation for test reports, Chinese medical language processing and computer-aided diagnosis. The opportunities and challenges to the development of laboratory medicine which taken from machine learning worth focusing.

关 键 词：机器学习 医学检验科学 医学信息学应用 模式识别 自动 

分 类 号：R446[医药卫生—诊断学]