MIT Creates AI that Predicts Depression from Speech
Depression is one of the most common disorders globally that impacts the lives of over 300 million people, and nearly 800,000 suicides annually, per the World Health Organization March 2018 figures. Diagnosing depression may be a challenging, complex endeavor. According to the Mayo Clinic, symptoms of depression varies, and doctors may use a physical exam, lab tests, psychiatric evaluation questionnaire, and criteria from the American Psychiatric Association's DSM-5 (Diagnostic and Statistical Manual of Mental Disorders), in order to determine a diagnosis of depression [1]. For a mental health professional, asking the right questions and interpreting the answers is a key factor in the diagnosis. But what if a diagnosis could be achieved through natural conversation, versus requiring context from question and answer?