AI can predict psychosis risk in everyday language

People's language could reveal clues about their future risk of developing psychosis. Scientists concluded this after studying the subtle features of people's everyday speech.

Researchers at Emory University in Atlanta, GA, and Harvard University in Boston, MA, used a machine-learning technique to analyze language in a group of at-risk young people.

They found that they could predict which individuals would go on to develop psychosiswith an accuracy of 93%.

A recent npj Schizophrenia study paper describes how the team developed and tested the method.

Senior study author Phillip Wolff, a professor of psychology at Emory University, explains that earlier research had already established that "subtle features of future psychosis are present in people's language." However, he noted, "we've used machine learning to actually uncover hidden details about those features."

He and his colleagues devised their machine-learning approach to measure two linguistic variables: semantic density and use of words relating to sound.

They concluded that "conversion to psychosis is signaled by low semantic density and talk about voices and sounds."

Low semantic density is a measure of what the team refers to as "poverty of content" or vagueness.

"This work," note the authors, "is a proof of concept study demonstrating that indicators of future mental health can be extracted from people's natural language using computational methods."

Machine learning and psychosis symptoms

Machine learning is a type of artificial intelligence in which computers "learn from experience" without scientists having to program the learning explicitly.

A machine-learning system looks for patterns in a known set of data and decides which patterns identify specific features. Having "learned" what these features are, it can then tirelessly identify them in a new set of data.

Machine learning can spot patterns in people's use of language that even doctors who have undergone training to diagnose and treat those at risk of psychosis may not notice.

"Trying to hear these subtleties in conversations with people is like trying to see microscopic germs with your eyes," explains first study author Neguine Rezaii, a fellow in the Department of Neurology at Harvard Medical School.

However, it is possible to use machine learning to find certain subtle patterns hiding in people's language. "It's like a microscope for warning signs of psychosis," she adds.

Source: Medical News Today