Researchers have developed a machine learning tool that can screen for co-morbid anxiety disorders and major depressive disorder using acoustic voice signals extracted from a one-minute verbal fluency test.
Researchers have developed machine learning tools that can screen for co-morbid anxiety disorders and major depressive disorder using acoustic voice signals. The team conducted a study involving participants with and without co-morbid anxiety disorders and major depressive disorder (AD/MDD). Participants were recorded using a secure telehealth platform while completing a semantic verbal fluency test, which required them to name as many animals as possible within a time limit.
The researchers extracted acoustic and phonemic features from the recordings and applied machine learning techniques to distinguish subjects with and without comorbid AD/MDD. The results demonstrated that a one-minute semantic verbal fluency test can be reliably used to screen for AD/MDD. This is particularly significant considering the mental health crisis in the United States, where a substantial portion of the population experiences AD or MDD, yet diagnosis and treatment rates remain disappointingly low.The study's authors, from the University of Illinois Urbana-Champaign, University of Illinois College of Medicine Peoria, and Southern Illinois University School of Medicine, believe this research holds promise for improving early detection and intervention for AD/MDD. They observed that individuals with comorbid AD/MDD tended to use simpler words, exhibited less variability in phonemic word length, and showed reduced levels of and variation in phonemic similarity compared to those without the condition. While the research team plans to further investigate the underlying biological mechanisms associated with these findings, they also aim to refine the model and explore its potential as a diagnostic tool. This will require collecting more extensive data from diverse populations and across various conditions. The ultimate goal is to develop a more accurate and comprehensive screening method that can effectively identify individuals struggling with AD/MDD and facilitate timely access to appropriate care
MACHINE LEARNING MENTAL HEALTH ACOUSTIC VOICE SIGNALS ANXIETY DISORDERS MAJOR DEPRESSIVE DISORDER CO-MORBIDITY SCREENING DIAGNOSIS TREATMENT
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