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Computer science researchers from the University of Rochester developed an app for health departments that uses natural language processing and artificial intelligence to identify likely food poisoning hot spots. Las Vegas health officials recently used the app, called nEmesis, to improve the city's inspection protocols and found it was 63% more effective at identifying problematic venues than the current state of the art. The researchers estimate that if every inspection in Las Vegas became adaptive, it could prevent over 9,000 cases of foodborne illness and 557 hospitalizations annually. The team presented the results at the 30th Association for the Advancement of Artificial Intelligence conference in February.
http://www.cs.rochester.edu/~sadilek/publications/Sadilek,%20Kautz,%20et%20al.%20Deploying%20nEmesis.pdf