1 Ocak 2024 Dergi makalesi Açık Erişim

Kizilay, Elif; Arslan, Berat; Verim, Burcu; Demirlek, Cemal; Demir, Muhammed; Cesim, Ezgi; Eyuboglu, Merve Sumeyye; Ozbek, Simge Uzman; Sut, Ekin; Yalincetin, Berna; Bora, Emre

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  <identifier identifierType="URL">https://aperta.ulakbim.gov.tr/record/276221</identifier>
  <creators>
    <creator>
      <creatorName>Kizilay, Elif</creatorName>
      <givenName>Elif</givenName>
      <familyName>Kizilay</familyName>
      <affiliation>Dokuz Eylul Univ, Hlth Sci Inst, Dept Neurosci, Izmir, Turkiye</affiliation>
    </creator>
    <creator>
      <creatorName>Arslan, Berat</creatorName>
      <givenName>Berat</givenName>
      <familyName>Arslan</familyName>
      <affiliation>Dokuz Eylul Univ, Hlth Sci Inst, Dept Neurosci, Izmir, Turkiye</affiliation>
    </creator>
    <creator>
      <creatorName>Verim, Burcu</creatorName>
      <givenName>Burcu</givenName>
      <familyName>Verim</familyName>
      <affiliation>Dokuz Eylul Univ, Hlth Sci Inst, Dept Neurosci, Izmir, Turkiye</affiliation>
    </creator>
    <creator>
      <creatorName>Demirlek, Cemal</creatorName>
      <givenName>Cemal</givenName>
      <familyName>Demirlek</familyName>
    </creator>
    <creator>
      <creatorName>Demir, Muhammed</creatorName>
      <givenName>Muhammed</givenName>
      <familyName>Demir</familyName>
      <affiliation>Dokuz Eylul Univ, Hlth Sci Inst, Dept Neurosci, Izmir, Turkiye</affiliation>
    </creator>
    <creator>
      <creatorName>Cesim, Ezgi</creatorName>
      <givenName>Ezgi</givenName>
      <familyName>Cesim</familyName>
      <affiliation>Dokuz Eylul Univ, Hlth Sci Inst, Dept Neurosci, Izmir, Turkiye</affiliation>
    </creator>
    <creator>
      <creatorName>Eyuboglu, Merve Sumeyye</creatorName>
      <givenName>Merve Sumeyye</givenName>
      <familyName>Eyuboglu</familyName>
      <affiliation>Dokuz Eylul Univ, Hlth Sci Inst, Dept Neurosci, Izmir, Turkiye</affiliation>
    </creator>
    <creator>
      <creatorName>Ozbek, Simge Uzman</creatorName>
      <givenName>Simge Uzman</givenName>
      <familyName>Ozbek</familyName>
      <affiliation>Dokuz Eylul Univ, Fac Med, Dept Psychiat, Izmir, Turkiye</affiliation>
    </creator>
    <creator>
      <creatorName>Sut, Ekin</creatorName>
      <givenName>Ekin</givenName>
      <familyName>Sut</familyName>
      <affiliation>Dokuz Eylul Univ, Fac Med, Dept Child &amp; Adolescent Psychiat, Izmir, Turkiye</affiliation>
    </creator>
    <creator>
      <creatorName>Yalincetin, Berna</creatorName>
      <givenName>Berna</givenName>
      <familyName>Yalincetin</familyName>
      <affiliation>Dokuz Eylul Univ, Hlth Sci Inst, Dept Neurosci, Izmir, Turkiye</affiliation>
    </creator>
    <creator>
      <creatorName>Bora, Emre</creatorName>
      <givenName>Emre</givenName>
      <familyName>Bora</familyName>
    </creator>
  </creators>
  <titles>
    <title>Automated Linguistic Analysis In Youth At Clinical High Risk For Psychosis</title>
  </titles>
  <publisher>Aperta</publisher>
  <publicationYear>2024</publicationYear>
  <dates>
    <date dateType="Issued">2024-01-01</date>
  </dates>
  <resourceType resourceTypeGeneral="Text">Journal article</resourceType>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://aperta.ulakbim.gov.tr/record/276221</alternateIdentifier>
  </alternateIdentifiers>
  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsIdenticalTo">10.1016/j.schres.20249.009</relatedIdentifier>
  </relatedIdentifiers>
  <rightsList>
    <rights rightsURI="http://www.opendefinition.org/licenses/cc-by">Creative Commons Attribution</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
  </rightsList>
  <descriptions>
    <description descriptionType="Abstract">&lt;p&gt;Identifying individuals at clinical high risk for psychosis (CHR-P) - P) is crucial for preventing psychosis and improving the prognosis for schizophrenia. Individuals at CHR-P may exhibit mild forms of formal thought disorder (FTD), making it possible to identify them using natural language processing (NLP) methods. In this study, speech samples of 62 CHR-P individuals and 45 healthy controls (HCs) were elicited using Thematic Apperception Test images. The evaluation involved various NLP measures such as semantic similarity, generic, and part-of-speech (POS) features. The CHR-P group demonstrated higher sentence-level semantic similarity and reduced mean image-to-text similarity. Regarding generic analysis, they demonstrated reduced verbosity and produced shorter sentences with shorter words. The POS analysis revealed a decrease in the utilization of adverbs, conjunctions, and first-person singular pronouns, alongside an increase in the utilization of adjectives in the CHR-P group compared to HC. In addition, we developed a machine-learning model based on 30 NLP-derived features to distinguish between the CHR-P and HC groups. The model demonstrated an accuracy of 79.6 % and an AUC-ROC of 0.86. Overall, these findings suggest that automated language analysis of speech could provide valuable information for characterizing FTD during the clinical high-risk phase and has the potential to be applied objectively for early intervention for psychosis.&lt;/p&gt;</description>
  </descriptions>
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