基于深度学习的环境健康跨领域危险因素挖掘分析  

Analysis of Cross-field Risk Factors of Environmental Health Based on Deep Learning

作　　者：陈松景[1] 李姣[1] 吴思竹[1] CHEN Song-ring;LI Jiao;WU Si-zhu(Institute of Information on Medicine, China Academy of Chinese Medical Sciences, Beijing 100020, P.R.C.)

机构地区：[1]中国医学科学院医学信息研究所,北京市朝阳区雅宝路3号100020

出　　处：《中国数字医学》2018年第6期21-24,共4页China Digital Medicine

基　　金：国家重点研发计划-重大疾病精准医学数据库群(编号:2016YFC0901602);中央级公益性科研院所基本科研业务费-空气污染数据与疾病数据关联挖掘方法研究(编号:2016ZX330020);中国医学科学院医学与健康科技创新工程-肿瘤生物样本库与精准医学大数据的深度挖掘与利用(编号:2017-I2M-2-003)~~

摘　　要：基于疾病与环境跨领域数据,针对细颗粒物、空气污染物和气象因素等多种危险因素,采用深度学习方法挖掘分析各分层人群发生呼吸系统疾病的危险因素,为特定人群有针对性地预防控制疾病提供依据,有助于公众提升自身疾病预防的意识。Based on the cross-field data of disease and environment, this paper is to analyze the risk factors of respiratory diseases in various stratified groups applies by deep learning method, and provide a basis for targeted prevention and control of diseases for specific groups, which can help the public to improve their awareness of disease prevention.

关 键 词：深度学习 环境健康 危险因素 跨领域 

分 类 号：R197.3[医药卫生—卫生事业管理]