A six-second voice clip is enough for new AI to diagnose type 2 diabetes.
The new test dubbed a ‘potential game-changer’ could screen for the disease by just saying a couple of sentences into your smartphone.
The study, published in the journal Mayo Clinic Proceedings: Digital Health, combines voice technology with artificial intelligence and could help identify millions of undiagnosed people with Type 2 diabetes.
The team from Klick Labs in Toronto, Canada claim their test is 89 percent accurate for women and 86 percent for men.
It works by using six to 10 seconds of people’s voices, along with basic health data, including age, sex, height, and weight, to create an AI model that can distinguish whether that person has Type 2 diabetes.
Researchers asked 267 people diagnosed as either non- or Type 2 diabetic to record a phrase into their smartphone six times daily for two weeks.
From more than 18,000 recordings, scientists analyzed 14 acoustic features for differences between non-diabetic and Type 2 diabetic individuals.
The team looked at a number of vocal features, like changes in pitch and intensity that can’t be perceived by the human ear.
Using signal processing, scientists were able to detect changes in the voice caused by Type 2 diabetes, vocal changes that were different for men and women.
Researcher Jaycee Kaufman, first author of the paper, said: “Our research highlights significant vocal variations between individuals with and without Type 2 diabetes and could transform how the medical community screens for diabetes.
“Current methods of detection can require a lot of time, travel, and cost. Voice technology has the potential to remove these barriers entirely.”
Almost half of the 480million adults living with diabetes worldwide are unaware they have the condition and nearly 90 percent of diabetic cases are Type 2 diabetes.
According to Diabetes UK, 4.3 million people in Britain have either type 1 or type 2 diabetes with another 2.4 million at high risk of developing the condition.
Type 2 is largely lifestyle-driven with bad diet and obesity two of the major factors behind it.
Professor Yan Fossat, vice president of Klick Labs and principal investigator of this study, said the non-intrusive and accessible approach offers the potential to screen vast numbers of people and help identify the large percentage of undiagnosed people with Type 2 diabetes.
He said: “Our research underscores the tremendous potential of voice technology in identifying Type 2 diabetes and other health conditions.
“Voice technology could revolutionize healthcare practices as an accessible and affordable digital screening tool.”
He added that it might also have applications to test for high blood pressure, prediabetes and women’s health.
Produced in association with SWNS Talker
