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Researchers trained an algorithm on thousands of voice recordings to spot subtle vocal indicators associated with diabetes. During initial testing, the model correctly identified type 2 diabetes in 82 percent of affected subjects after analyzing a 20 second reading clip. While promising as a preliminary screening tool, formal medical testing remains essential for diagnosis.