Talk to your Robo-Doctor: New Study Shows AI Can Detect Type 2 Diabetes Just by Listening
New medical research has revealed an exciting breakthrough in the field of artificial intelligence (AI). According to a study conducted by Klick Labs and published in “Mayo Clinic Proceedings: Digital Health,” AI technology can detect type 2 diabetes simply by analyzing a patient’s voice for as little as six to ten seconds. The study showed an impressive 89% accuracy rate for women and 86% accuracy rate for men.
Lead author Jaycee Kaufman explained, “Our research has identified significant vocal variations between individuals with and without Type 2 diabetes. This has the potential to revolutionize how we screen for this condition within the medical community. Unlike current detection methods that are time-consuming and costly, voice technology can eliminate these barriers entirely.”
During the study, researchers collected vocal recordings from 267 individuals, both with and without type 2 diabetes, who were asked to record specific phrases on their smartphones six times a day for a two-week period. Over 18,000 recordings were analyzed for more than 14 acoustic features, revealing noticeable differences between diabetic and non-diabetic individuals. Participants also shared basic health data such as age, height, and weight.
Signal processing technologies were used to detect subtle vocal pitch variations that are imperceptible to the human ear. These hidden acoustic clues proved to be crucial in accurately identifying type 2 diabetes. Yan Fossat, Klick VP and principal investigator, highlighted the potential of voice technology in healthcare, stating, “Our research demonstrates the tremendous potential of voice technology in the identification of type 2 diabetes and other health conditions.”
Furthermore, researchers discovered that the AI diabetes detector achieved close to 90% accuracy after analyzing patients’ voices, solidifying the efficacy of this innovative approach. The possibilities are vast as voice technology could transform healthcare practices into a more accessible and affordable screening tool.
Klick’s next step is to replicate the study and expand the use of vocal search to detect pre-diabetes, hypertension, and other health conditions. This latest breakthrough comes on the heels of a recent MIT discovery of a bio-implant that molds itself more seamlessly to the body, improving the delivery of essential medications like insulin.
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