Predictive AI applications are relatively new to mental and behavioral health, but are already showing a lot of promise. In a recent publication on detecting suicide risk through analyzing text messages, UW Medicine researchers found that algorithms performed as well as trained evaluators. This is great news for predictive AI and the ability to save lives at risk for suicide through data analysis in real-time, when and where the individual is located. This is important because some healthcare providers may be concerned when they communicate by text message with a patient, they might miss something they are trained to pick up from voice inflection, facial expression, and other auditory or physical signals. Algorithms like this can help enhance the provider's ability to analyze the patient when communicating by text, an increasingly popular way for people to access mental health.

A new study at Georgia State University's TReNDS Center may result in the early detection of debilitating diseases such as Alzheimer's, schizophrenia, and autism. The findings of this study were published in the Journal of Scientific Reports. A team of seven Georgia State scientists created a sophisticated computer program that could sift through massive amounts of brain imaging data and uncover unexpected patterns related to mental health disorders. The brain imaging data is produced by functional magnetic resonance imaging (fMRI) scans, which evaluate dynamic brain activity by detecting minute variations in blood flow. "We constructed artificial intelligence models to analyze the substantial volumes of information from fMRI," said Sergey Plis, the study's lead author and an associate professor of computer science and neuroscience at Georgia State University.

The advances in AI has enabled computers to assist doctors in detecting diseases and help keep a check on patient health remotely. Now, researchers from the University of Colorado Boulder (CU Boulder) are working to leverage ML to psychiatry using a speech-based mobile app. Peter Foltz, a research professor at the Institute of Cognitive Science says – "We are not in any way trying to replace clinicians. But we do believe we can create tools that will allow them to better monitor their patients." Notably, he is also the co-author of a new paper in Schizophrenia Bulletin that illustrates the promise and potential pitfalls of artificial intelligence in psychiatry.