Researchers from Klick Labs have developed an artificial intelligence (AI) model that can detect type 2 diabetes by analyzing a person's voice. The AI tool, combined with basic health information, was 89% accurate in diagnosing type 2 diabetes in women and 86% accurate in men. Changes in vocal characteristics, such as pitch and strength, can indicate diabetic neuropathy or nerve damage associated with diabetes. While more research is needed to validate the effectiveness of this method across different populations and factors, the AI voice test shows promise as a non-intrusive and accessible screening tool for diabetes.
A tablet-based screening application called SenseToKnow has shown promise in improving early detection of Autism Spectrum Disorder (ASD), according to a study funded by the National Institutes of Health. The app demonstrated 87.8% sensitivity and 80.8% specificity in detecting ASD, accurately identifying toddlers who may require further investigation. By reducing disparities in early diagnosis and intervention, the app could ensure that children and families receive the necessary support. The study highlights the importance of developing accurate ASD screening tools and linking positive screening results to appropriate referrals and services.
AI algorithms can predict whether patients will develop pancreatic cancer up to three years before doctors can make the same diagnosis, according to a study published in Nature. Researchers trained AI algorithms on millions of medical records obtained in the Danish National Patient Registry and the US Veterans Affairs Corporate Data Warehouse. The software cannot yet be used to run screening programs, but the team believes that as the technology improves and operating costs decrease, AI could become a valuable screening tool in the future.
AI algorithms can predict pancreatic cancer up to three years before human doctors, according to a study published in Nature. The researchers trained AI models on millions of medical records to correlate diagnosis codes to pancreatic cancer. The most effective model showed that out of the top 1,000 highest-risk patients over 50, about 320 would go on to develop pancreatic cancer. The study is still in its early stages, and the software cannot yet be used to run screening programs. However, the team believes that as the technology improves and operating costs decrease, AI could become a valuable screening tool in the future.
