Nearly half of adults with diabetes remain undiagnosed, particularly in low- and middle-income countries where access to diabetes tests is limited. However, a breakthrough in artificial intelligence (AI) technology by Klick Labs has the potential to change this. They have developed an AI system that can accurately detect type 2 diabetes with up to 89% accuracy by analyzing a person’s voice, making it a more accessible screening tool than standard blood tests.
In a recent study conducted by Klick Labs, participants were asked to record voice samples multiple times a day for two weeks. The AI model then analyzed differences in pitch, intensity, jitter, and shimmer to detect diabetes. This innovative approach takes advantage of the fact that changes in voice patterns can indicate various health conditions, including diabetes, voice disorders, respiratory disorders, neurologic disorders, and mood disorders.
Interestingly, the accuracy of the AI system varies between men and women. Different voice features predict diabetes in each gender. However, further research is needed to validate its effectiveness in larger and more diverse populations. Nonetheless, Klick Labs has made significant progress in identifying biomarkers in everyday speech to predict health conditions like Type 2 diabetes.
The research conducted by Klick Labs, which was published in Mayo Clinic Proceedings – Digital Health, demonstrates that combining just a few seconds of a person’s voice with basic health data can accurately identify if someone has Type 2 diabetes. This breakthrough has the potential to enable early detection and intervention for diabetes, reducing barriers to diagnosis and empowering individuals to take proactive steps toward their well-being.
Type 2 diabetes can cause subtle changes in voice quality, pitch, and other acoustic features due to its impact on the vocal apparatus. Leveraging advanced machine learning techniques, Klick Labs trained their predictive model on vocal samples and analyzed patterns to identify markers indicative of diabetes. This research has the potential to revolutionize diabetes diagnosis, making it more accessible and efficient.
Klick Labs’ AI system that detects type 2 diabetes through voice analysis can potentially transform how diabetes is diagnosed. With nearly half of adults with diabetes remaining undiagnosed, particularly in low- and middle-income countries, this breakthrough technology provides a more accessible screening tool. Combining just a few seconds of a person’s voice with basic health data, the AI system can accurately identify if someone has Type 2 diabetes. This research has the potential to enable early detection and intervention, reducing barriers to diagnosis and empowering individuals to prioritize their well-being.
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