Data-driven, automated machine-learning system for detecting emerging public health threats

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Data-driven, automated machine-learning system for detecting emerging public health threats

A dire threat to public health can emerge from a huge variety of sources—for example, infectious diseases, a spate of drug overdoses, or exposures to toxic chemicals. Federal, state, and local health departments must respond rapidly to disease outbreaks and other emerging bio-threats. While the current automated systems for “syndromic surveillance” can help by monitoring health data and detecting disease clusters, they are not able to detect clusters with rare or previously unseen symptomology.

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