Big Data Analytics for Risk Factor Surveillance

Xiaoquan Yao


Background: Risk factor surveillance is a con nuous data collec on, analysis, and  dissemina  on  ac  vity.  Informa on technology plays an important role in building the surveillance system and a big data approach has become a hot topic. Big data analy cs are the advanced methods to derive insight and knowledge from the big data of high volume, speed and variety, such as text mining, natural language processing, and ar ficial intelligence. They can handle a large amount of untradi onal and unstructured data and thus provide innova ve ways for conduc ng the risk factor surveillance. Purpose: The purpose of this study is to explore the possible applica on of current big data analy  cs in the risk factor surveillance.

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