Malnutrition threat reduced by AI technology, research shows
A new study in Canada shows that AI technology can outperform staff when it comes to monitoring the nutrient intake of residents in long-term care.
Checking whether residents are eating the right diet is currently down to staff members, which Robert Amelard, a postdoctoral fellow at University Health Network, who is involved in the research, said leads to an ‘error rate of 50% or more’.
In a bid to reduce the error levels researchers at the University of Waterloo, the Schlegel-UW Research Institute for Aging and the University Health Network, worked with long-term care workers and dietitians to pioneer a smart system that uses AI to assess the plates of food eaten by each resident, with the software able to calculate what food has been consumed and its nutritional value.
“Right now, there is no way to tell whether a resident ate only their protein or only their carbohydrates,” said Kaylen Pfisterer, who co-led the research while earning a PhD in systems design engineering at Waterloo. “Our system is linked to recipes at the long-term care home and, using artificial intelligence, keeps track of how much of each food was eaten to make sure residents are meeting their specific nutrient requirements.”
Which is vital because, according to most estimates, more than half of long-terms care residents are either malnourished or are a high risk. So with an accuracy rate in calculating what residents are actually eating of 5%, the new AI technology system has the potential to be truly transformative.
The next step is for the system to be integrated into tablet computers used by staff to maintain electronic records.
“My vision would be to monitor and leverage any changes in food intake trends as yellow or red flags for the health status of residents more generally and for monitoring infection control,” added Pfisterer.
Original content from Innovators Magazine Online. Note: Content has been edited for style and length.