AI can detect anxiety and depression in a child's speech

The study conducted by researchers at the University of Vermont in the USA suggests a machine learning algorithm might provide a fast and easy way of diagnosing anxiety and depression – conditions that are difficult to spot and often overlooked in young people. "We need quick, objective tests to catch kids when they are suffering," said study lead author Ellen McGinnis, who is a clinical psychologist at the university's Medical Centre's Vermont Centre for Children, Youth and Families. "The majority of kids under eight are undiagnosed," she added. Early diagnosis of these conditions is critical as children respond well to treatment while their brains are still developing, according to the researchers, but if they are left untreated they are at greater risk of substance abuse and suicide later in life. Standard diagnosis involves a 60-90-minute semi-structured interview with a trained clinician and their primary caregiver. McGinnis, along with University of Vermont biomedical engineer and study senior author Ryan McGinnis, have been looking at ways to overcome this, by using artificial intelligence and machine learning to make diagnosis faster and more reliable.