Automated speech analysis techniques, when combined with artificial intelligence and
machine learning, show potential in capturing and predicting a wide range of psychosis …

Preventing relapse in schizophrenia improves long-term health outcomes. Repeated
episodes of psychotic symptoms shape the trajectory of this illness and can be a detriment to …

Deviations in syntax production have been well documented in schizophrenia spectrum
disorders (SSD). Recently, we have shown evidence for transdiagnostic subtypes of …

Abstract Background and Hypothesis Speech markers are digitally acquired,
computationally derived, quantifiable set of measures that reflect the state of neurocognitive …

Abstract Language-related symptoms, such as disorganized, impoverished speech and
communicative behaviors, are one of the core features of schizophrenia. These features …

Depression and some other illnesses are associated with increased self-reference and
negative emotion in language. Research findings on lexical patterns in Borderline …

Background People with schizophrenia exhibit notable difficulties in the use of everyday
language, which directly impacts one's ability to complete education and succeed in …

As mental health care systems worldwide struggle to meet demand, there is increasing focus
on using language models (LM) to infer neuropsychiatric conditions or psychopathological …

Background Individuals at clinical high risk (CHR) for psychosis experience subtle emotional
disturbances that are traditionally difficult to assess, but natural language processing (NLP) …

As recently highlighted in the New England Journal of Medicine, 1, 2 artificial intelligence
(AI) has the potential to revolutionize the field of medicine. While AI undoubtedly represents …