AIMS: In this proof-of-principle study, our aim was to test automated speech analyses
combined with Machine Learning to predict later psychosis onset in youths at clinical high …

Language and speech are the primary source of data for psychiatrists to diagnose and treat
mental disorders. In psychosis, the very structure of language can be disturbed, including …

Recent work has suggested that disorganised speech might be a powerful predictor of later
psychotic illness in clinical high risk subjects. To that end, several automated measures to …

The language and speech of individuals with psychosis reflect their impairments in cognition
and motor processes. These language disturbances can be used to identify individuals with …

Automated extraction of quantitative linguistic features has the potential to predict objectively
the onset and progression of psychosis. These linguistic variables are often considered to …

Subtle features in people's everyday language may harbor the signs of future mental illness.
Machine learning offers an approach for the rapid and accurate extraction of these signs …

Individuals with serious mental illness experience changes in their clinical states over time
that are difficult to assess and that result in increased disease burden and care utilization. It …

Background Clinicians routinely use impressions of speech as an element of mental status
examination. In schizophrenia-spectrum disorders, descriptions of speech are used to …

Background Formal thought disorder is a cardinal feature of psychotic disorders, and is also
evident in subtle forms before psychosis onset in individuals at clinical high-risk for …

Computerized natural language processing (NLP) allows for objective and sensitive
detection of speech disturbance, a hallmark of schizophrenia spectrum disorders (SSD). We …