New York, Scientists are now working to apply Artificial Intelligence (AI) to psychiatry, with a speech-based mobile app that can categorize a patient’s mental health status as well as or better than a human can.
“We are not in any way trying to replace clinicians,” said Peter Foltz, research professor at the Institute of Cognitive Science at University of Colorado at Boulder.
“But we do believe we can create tools that will allow them to better monitor their patients,” he added in a paper published in Schizophrenia Bulletin.
Even when a patient does make it in for an occasional visit, therapists base their diagnosis and treatment plan largely on listening to a patient talk – an age-old method that can be subjective and unreliable, notes paper co-author Brita Elvevåg, a cognitive neuroscientist at the University of Tromsø, Norway.
“Humans are not perfect. They can get distracted and sometimes miss out on subtle speech cues and warning signs,” Elvevåg says. “Unfortunately, there is no objective blood test for mental health.”
To make progress on this, Brita Elvevag, a cognitive neuroscientist at the University of Tromso, Norway, and Foltz teamed up to develop machine learning technology able to detect day-to-day changes in speech that hint at mental health decline.
For instance, sentences that don’t follow a logical pattern can be a critical symptom in schizophrenia.
Shifts in tone or pace can hint at mania or depression. And memory loss can be a sign of both cognitive and mental health problems.
“Language is a critical pathway to detecting patient mental states,” said Foltz.
“Using mobile devices and AI, we are able to track patients daily and monitor these subtle changes.”
The new mobile app asks patients to answer a 5- to 10-minute series of questions by talking into their phone.
Among various other tasks, they’re asked about their emotional state, asked to tell a short story, listen to a story and repeat it and given a series of touch-and-swipe motor skills tests.
In one recent study, the team asked human clinicians to listen to and assess speech samples of 225 participants — half with severe psychiatric issues and half healthy volunteers.
They then compared those results to those of the machine learning system.
“We found that the computer’s AI models can be at least as accurate as clinicians,” Foltz noted.
If the app detected a worrisome change, it could notify the patient’s doctor to check in, the researchers noted.
