Voice Technology and AI Combine to Detect Type 2 Diabetes, According to Klick Labs Study
Klick Labs has unveiled an innovative method that uses voice technology and artificial intelligence (AI) to detect Type 2 diabetes, according to a recent study. The research involved analyzing short voice recordings and basic health information to train an AI model to identify the disease. The model achieved an accuracy rate of 89 percent for women and 86 percent for men.
The study, which involved 267 participants classified as non-diabetic or Type 2 diabetic, instructed individuals to record a specific phrase on their smartphones six times a day for two weeks. Researchers analyzed over 18,000 audio recordings and studied 14 acoustic features to distinguish between non-diabetic and diabetic individuals.
Jaycee Kaufman, the first author of the paper and a research scientist at Klick Labs, emphasized the potential of this research in transforming diabetes screening methods. Current detection methods often require significant time, expense, and travel, but voice technology offers a streamlined and accessible alternative.
The research focused on various vocal attributes, including imperceptible alterations in pitch and intensity. Signal processing techniques were used to capture voice changes associated with Type 2 diabetes, with variations manifesting differently in males and females.
Globally, nearly half of the 240 million adults with diabetes are unaware of their condition, and Type 2 diabetes accounts for approximately 90 percent of cases, according to the International Diabetes Federation. Traditional diagnostic tests for prediabetes and Type 2 diabetes typically involve visiting a healthcare provider for the glycated hemoglobin (A1C) test, fasting blood glucose (FBG) test, or the OGTT.
Klick Labs’ non-invasive approach to screening aims to identify undiagnosed cases of Type 2 diabetes in large populations. The method offers a more accessible and affordable digital screening tool.
Yan Fossat, Vice President of Klick Labs and principal investigator of the study, highlighted the potential of voice technology in healthcare. Fossat stated that voice technology has the ability to revolutionize healthcare practices by serving as an accessible and affordable digital screening tool. The study also outlined future steps, including replicating the research and expanding into voice-based diagnostics for prediabetes, women’s health, and hypertension.
Klick Labs has been investing in machine learning, data science, and AI for over a decade, with a specific focus on diabetes research. Their latest study was published in Mayo Clinic Proceedings: Digital Health.
Overall, this groundbreaking study by Klick Labs demonstrates the potential of using voice technology and AI to detect Type 2 diabetes. With its high accuracy rates and non-invasive approach, this innovative method has the potential to revolutionize diabetes screening and improve access to healthcare.
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