Artificial intelligence (AI) could in future be used to comb restaurant reviews for possible sources of foodborne illness and stop more people becoming sick.

Scientists at the UK Health Security Agency (UKHSA) have assessed a range of AI models for their ability to trawl thousands of online reviews for information about symptoms which might relate to outbreaks of gastrointestinal (GI) illness such as diarrhoea, vomiting and abdominal pain, as well as different food types people report eating.

The tests showed promising results leading scientists to believe this information could one day be used to identify and potentially target investigations into foodborne illness outbreaks.

The works forms part of UKHSA’s evaluation of the ability of AI to perform different tasks within public health.

Foodborne GI illness causes millions of people to become unwell every year, but it is estimated that most cases are not formally diagnosed.

Scientists believe that using AI to gather information from customer reviews could one day become routine, providing more information on rates of GI illness which are not captured by current systems as well as vital clues around possible sources and causes in outbreaks.

They did however identify a range of challenges that would first need to be overcome. Although it’s possible to gather general information on the type of food people have eaten and which may be linked to illness, determining which specific ingredients or other factors that may be linked is difficult. Variations in spelling and the use of slang were also identified as potential challenges, as well as people misattributing their illness to a given meal.

“We are constantly looking for new and effective ways to enhance our disease surveillance,” said Professor Steven Riley, chief data officer at UKHSA. “Using AI in this way could soon help us identify the likely source of more foodborne illness outbreaks, in combination with traditional epidemiological methods, to prevent more people becoming sick.”