Real-time processing of social media with SENTINEL: A syndromic surveillance system incorporating deep learning for health classification
作者:
Highlights:
• End to End software system built with open source tools for real-time processing of public social media data.
• Event detection and Situational Awareness of disease outbreaks.
• Development of a classifier for isolating health-related tweets using deep neural networks.
• Nowcasting for multiple diseases based on the syndromic surveillance data.
摘要
•End to End software system built with open source tools for real-time processing of public social media data.•Event detection and Situational Awareness of disease outbreaks.•Development of a classifier for isolating health-related tweets using deep neural networks.•Nowcasting for multiple diseases based on the syndromic surveillance data.
论文关键词:Real-time processing,Classification,Clustering,Event detection,68T50,68T05,62M20
论文评审过程:Received 31 May 2017, Revised 31 January 2018, Accepted 28 April 2018, Available online 1 June 2018, Version of Record 7 March 2019.
论文官网地址:https://doi.org/10.1016/j.ipm.2018.04.011