Machine learning techniques and research framework in foodborne disease surveillance system

Abstract Based on the verified application in China's National Foodborne Disease Outbreak Surveillance System, machine learning techniques have been indicated to have very positive effects. We summarize current positive attempts on improving case reporting, helping diagnosing and outbreak prediction. Based on the attempts, we propose a general framework to facilitate future improvements for a more intelligent foodborne disease surveillance system, which can greatly help human health.