Researchers at the University of Rochester have unveiled an innovative AI-powered screening tool designed to detect early signs of Parkinson’s disease through speech analysis. This user-friendly tool requires individuals to record two short sentences, which the AI then analyzes for vocal patterns indicative of the disease. Backed by extensive acoustic models trained on millions of recordings, the tool boasts an impressive 85% accuracy rate. Vocal changes, such as soft speech and monotone delivery, are recognized as key early indicators of Parkinson’s, according to the Parkinson’s Foundation. The aim is to integrate this tool with other motor control symptom screenings, making it accessible, especially for those in remote areas. However, researchers stress that it should not replace clinical diagnoses but serves as a preliminary check to identify possible neurological issues. The findings are detailed in the journal NPJ Parkinson’s Disease, marking a significant advancement in digital health and early disease detection.
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