Artificial Intelligence for infectious disease Big Data Analytics

被引：110
|
作者：
Wong, Zoie S. Y. [1 ]
Zhou, Jiaqi [2 ]
Zhang, Qingpeng [2 ]
机构：
[1] St Lukes Int Univ, Grad Sch Publ Hlth, Tokyo 1040045, Japan
[2] City Univ Hong Kong, Dept Syst Engn & Engn Management, Hong Kong, Peoples R China
来源：
INFECTION DISEASE & HEALTH | 2019年 / 24卷 / 01期
基金：
日本学术振兴会; 中国国家自然科学基金;
关键词：
Infectious diseases modelling; Emergency response; Artificial Intelligence; Machine learning; HEALTH-CARE;
D O I：
10.1016/j.idh.2018.10.002
中图分类号：
R1 [预防医学、卫生学];
学科分类号：
1004 ; 120402 ;
摘要：
Background: Since the beginning of the 21st century, the amount of data obtained from public health surveillance has increased dramatically due to the advancement of information and communications technology and the data collection systems now in place. Methods: This paper aims to highlight the opportunities gained through the use of Artificial Intelligence (AI) methods to enable reliable disease-oriented monitoring and projection in this information age. Results and Conclusion: It is foreseeable that together with reliable data management platforms AI methods will enable analysis of massive infectious disease and surveillance data effectively to support government agencies, healthcare service providers, and medical professionals to response to disease in the future. (C) 2018 Australasian College for Infection Prevention and Control. Published by Elsevier B.V. All rights reserved.
引用
收藏
页码：44 / 48
页数：5
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