Leveraging computational linguistics and machine learning for detection of ultra-high risk of mental health disorders in youths

Key findings

To the best of our knowledge, this is the first study to examine the value of speech-derived sentiment and linguistic features in detecting UHR. We found that features capturing sentiment variability (i.e., EVA), lexical…