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dc.rights.licenseCC-BY-NC-ND
dc.contributor.advisorWijnen, Frank
dc.contributor.authorBrueijs, Sabine de
dc.date.accessioned2023-05-02T00:00:42Z
dc.date.available2023-05-02T00:00:42Z
dc.date.issued2023
dc.identifier.urihttps://studenttheses.uu.nl/handle/20.500.12932/43832
dc.description.abstractDiagnosing psychiatric conditions is not completely objective, leaving much room for misdiagnosis to occur. Part of what causes this, is the absence of biomarkers for psychiatric conditions. In recent years, efforts have been made to find biomarkers for schizophrenia and psychosis based on expressive language. Here, an overview of studies on this topic from the past five years (2017-2022) is provided. The research questions were “Can the form and content of expressive language be used to help diagnose schizophrenia?” and “What aspects of expressive language are the most informative regarding assessment of risk of conversion to psychosis?”. The results of the literature search suggest analysis of expressive language can be used to recognize schizophrenia in individual patients and to assess whether someone is close to experiencing a psychotic episode. In addition, it seems that mainly semantics and discourse organization are of interest. However, there are indications that findings of studies may be poorly generalizable over languages and individuals. This is a problem that needs to be solved before language can be reliably used as a biomarker in the clinical practice.
dc.description.sponsorshipUtrecht University
dc.language.isoEN
dc.subjectEen literatuuronderzoek naar het gebruik van informatie over taalgebruik en -inhoud van mensen bij het vaststellen of ze schizofrenie hebben en wat hun risico op een psychose is.
dc.titleSearching for Biomarkers: On Using Form and Content of Expressive Language in Diagnosis of Schizophrenia and Assessment of Risk of Psychosis
dc.type.contentMaster Thesis
dc.rights.accessrightsOpen Access
dc.subject.keywordsnatural language processing; biomarkers; schizophrenia; psychosis; review
dc.subject.courseuuNeuroscience and Cognition
dc.thesis.id16240


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