Clinical use of semantic space models in psychiatry and neurology: A systematic review and meta-analysis

J. N. de Boer*, A. E. Voppel, M. J. H. Begemann, H. G. Schnack, F. Wijnen, I. E. C. Sommer

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

35 Citations (Scopus)

Abstract

Verbal communication disorders are a hallmark of many neurological and psychiatric illnesses. Recent developments in computational analysis provide objective characterizations of these language abnormalities. We conducted a meta-analysis assessing semantic space models as a diagnostic or prognostic tool in psychiatric or neurological disorders. Diagnostic test accuracy analyses revealed reasonable sensitivity and specificity and high overall efficacy in differentiating between patients and controls (n=1680: Hedges' g=.73, p=.001). Analyses of full sentences (Hedges' g=.95 p

Original languageEnglish
Pages (from-to)85-92
Number of pages8
JournalNeuroscience and Biobehavioral Reviews
Volume93
DOIs
Publication statusPublished - Oct-2018

Keywords

  • Natural language processing
  • Vector space
  • Semantic space
  • Neurology
  • Psychiatry
  • AUTISM SPECTRUM DISORDER
  • LANGUAGE COMPREHENSION
  • AUTOMATED-ANALYSIS
  • SPEECH
  • SCHIZOPHRENIA
  • PSYCHOSIS
  • DISCOURSE
  • COHERENCE
  • FEATURES
  • DEFICITS

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