In the prevailing there’s-an-app-for-that culture, perhaps it should not be surprising that researchers are exploring machine learning that could bring artificial intelligence to the practice of psychiatric diagnosis.
Peter Foltz, a research professor at the Institute of Cognitive Science at the University of Colorado Boulder, is co-author on a new paper in Schizophrenia Bulletin that lays out the potential payoffs and possible pitfalls of AI in psychiatry.
And, with co-author Brita Elvevåg, a cognitive neuroscientist at the University of Tromsø, Norway, Foltz is striving to apply machine learning — a subset of AI — to psychiatry through a speech-based mobile app that can categorize a person’s mental health status just as well, or even better, than a human clinician can.
“The goal is not to replace what a clinician does,” Foltz said. “The goal is to be able to give them better tools to help access more information about their patients.”
Foltz said he and Elvevåg met a number of years ago at a conference where he was giving a talk about how to analyze coherence in language using technology, and she was doing research in schizophrenia at the National Institute of Mental Health.