As rates of mental health conditions like depression spike, we desperately need new ways of identifying and treating people in distress. The last big breakthrough in treating depression was all the way back in the 1980s. That was when Prozac, the first SSRI antidepressant, was released. It and its subsequent copycats soon swept the globe, and hundreds of millions of people have now taken this kind of medication. But while three-quarters of people say the pills have helped them feel better, they don't work for everyone.

Scientists are now developing an Artificial Intelligence System that can recognize signs of depression and anxiety in children. It does it by studying their speech patterns, and so far it has show to be over 80% accurate. There are many issues in the field of child psychiatry, including insurance problems, long waits for appointments and an overall failure to recognize the early or major symptoms of issues with children. For that reason, doctors are looking at new technology that could help them solve some or most of these problems. You can read the full article at: https://bit.ly/2HPf40N

Scientists in multiple fields of psychology are actively gathering data and undergoing testing in an effort to teach artificial intelligence programs to diagnose mental illness in humans. This is according to a report in The Verge written by B. David Zarley, who himself has borderline personality disorder, as part of its Real World AI issue. Zarley met with multiple scientists who are each taking their own approach to machine learning in the service of finding a better way to diagnose psychological disorders. Sponsored adThis sponsor paid to have this advertisement placed in this section. The current model, based on referring to the DSM to guide psychiatrists to make diagnoses around a patient's self-reported symptoms, is inherently biased and considered by many in the field of psychology to be flawed.