Scientists at Emory University in Atlanta developed an algorithm, trained to recognize common patterns of speech using thousands of Reddit posts, that could quantify an individual’s semantic density, a known indicator of psychosis. In the process of using the algorithm to analyze the speech patterns of individuals with and without symptoms of psychosis, the scientists discovered another, previously unknown indicator: the frequent use of words associated with voices and sounds.
As a result, when both semantic density and the use of sound-related words were taken into account, the algorithm was able to predict the emergence of psychosis with 93 percent accuracy. In contrast, clinicians are able to predict psychosis in those with prodromal syndrome with about 80 percent accuracy.
“The automated technique we’ve developed is a really sensitive tool to detect these hidden patterns. It’s like a microscope for warning signs of psychosis,” Neguine Rezaii, MD, first author of the paper, said. “In the clinical realm, we often lack precision…We need more quantified, objective ways to measure subtle variables, such as those hidden within language usage.”
More articles about AI:
Community Health Network adopts voice recognition tool to automate clinical documentation
AMA updates recommendations for medical AI usage
Machine learning outperforms human dermatologists in diagnosing pigmented skin lesions
Becker’s 3rd Annual Fall Chief Pharmacy Officer Summit is the top tier event that the people leading the future of pharmacy convene. This 3-day event is built specifically for Chief Pharmacy Officers and senior pharmacy leaders. The sessions examine the workforce, financial and clinical priorities shaping pharmacy today. Becker’s is where candid discussions flourish and new ideas thrive. Becker's 3rd Annual Fall Chief Pharmacy Officer Summit
