Google may soon tell you restaurants that are likely to be food poisoning, thanks to a new smart algorithm, as well as collaboration with researchers from Harvard University.

According to the US site Engadget, by working with Harvard researchers, Google conducted a machine-learning test in Chicago and Las Vegas to identify user search queries for things like "stomach cramps" or "diarrhea", linked to site data – in particular Recently visited restaurants – Smartphones used to conduct these searches.

Health inspectors were sent to a number of restaurants referred to as "Google" as unsafe, others identified by traditional methods, such as consumer complaints. When researchers compared the model to routine inspection by health departments in Las Vegas and Chicago, they found that the average The total accuracy of all unsafe restaurants detected by the model was 52.3 percent, while the overall rate of detection of unsafe restaurants through routine inspections across the two cities was 22.7 percent.

The model can play a key role in combating the ongoing problem of foodborne diseases, said Evgeny Gabrilovic, co-author and research scientist at Google.

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