AI algorithm detects childhood depression

Anxiety and depression are inherently tricky conditions to diagnose, with clinicians turning to exams and questionnaires to make their assessments. For this reason, the search is on for clearer, more straightforward ways to identify the conditions, and scientists at the University of Vermont believe they have unearthed another with the help of a newly-developed AI algorithm that can detect telltale signals in a subject’s speech. The new research makes use of a machine learning algorithm tuned to detect markers of depression and anxiety through the speech of young children, conditions known together as “internalizing disorders.”