An international team of researchers, including a core group of IBM computer scientists, has successfully tested a machine learning algorithm that can accurately predict whether a person will develop psychosis by simply analyzing their speech patterns.

The IBM Research team for Computational Psychiatry and Neuroimaging has been working for some time to develop a way to accurately evaluate the psychiatric state of a patient using speech samples. An initial study published in 2015 demonstrated an extraordinary rate of success in early testing, but larger, and more expansive, work was necessary to further develop the system.

Now in a new study involving a larger cohort and a different evaluation protocol, the system was able to effectively predict the onset of psychosis within two years in at-risk subjects, with an accuracy rate of around 80 percent. The study was the result of an international collaboration with Mt. Sinai School of Medicine, Columbia University, UCLA and the Universities of Melbourne, Australia, and Buenos Aires, Argentina.

The system examined transcripts of interviews with subjects identified as at-risk of developing psychosis, about one quarter of which went on to develop a psychotic disorder over the following two years. The subjects were asked to explain how well they understood a short story they were given to read and the algorithm examining the speech patterns of the subjects was able to determine, with 83 percent accuracy, whether a person would go on to develop a psychosis.

"There are now novel computerized methods to characterize complex behaviors such as language," explains lead author on the study Cheryl Corcoran, from Mount Sinai School of Medicine. "Speech is easy to collect and inexpensive to analyze using computer-based analysis. This technology could be applied across psychiatry, and plausibly in other fields of medicine."

The broad applications for the technology are certainly in IBM's sights with Guillermo Cecchi, from the IBM Research team, suggesting that similar computer-driven diagnostic analysis of speech patterns is being studied for conditions including Parkinson's, Alzheimer's and depression. The ultimate goal would be the development of some kind of diagnostic app that could track a person's speech patterns and suggest risk warnings for a variety of mental diseases.

"In five years, what we say and write will be used as indicators of our mental health and physical wellbeing," Cecchi suggests. "Patterns in our speech and writing analyzed by cognitive systems will provide tell-tale signs of early-stage mental disease that prompt us to seek treatment."

The study was published in the journal World Psychiatry.

Source: IBM Research

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