Literature DB >> 1556562

Natural language processing in psychiatry. Artificial intelligence technology and psychopathology.

D A Garfield1, C Rapp, M Evens.   

Abstract

The potential benefit of artificial intelligence (AI) technology as a tool of psychiatry has not been well defined. In this essay, the technology of natural language processing and its position with regard to the two main schools of AI is clearly outlined. Past experiments utilizing AI techniques in understanding psychopathology are reviewed. Natural language processing can automate the analysis of transcripts and can be used in modeling theories of language comprehension. In these ways, it can serve as a tool in testing psychological theories of psychopathology and can be used as an effective tool in empirical research on verbal behavior in psychopathology.

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Year:  1992        PMID： 1556562     DOI： 10.1097/00005053-199204000-00004

Source DB:  PubMed          Journal:  J Nerv Ment Dis        ISSN： 0022-3018            Impact factor:   2.254


  5 in total

1.  Using electronic medical records to enable large-scale studies in psychiatry: treatment resistant depression as a model.

Authors:  R H Perlis; D V Iosifescu; V M Castro; S N Murphy; V S Gainer; J Minnier; T Cai; S Goryachev; Q Zeng; P J Gallagher; M Fava; J B Weilburg; S E Churchill; I S Kohane; J W Smoller
Journal:  Psychol Med       Date:  2011-06-20       Impact factor: 7.723

2.  Training residents in psychotherapy for psychotic patients : curricular constraints and clinical suggestions.

Authors:  D A Garfield
Journal:  Acad Psychiatry       Date:  1994-09

Review 3.  Text mining applications in psychiatry: a systematic literature review.

Authors:  Adeline Abbe; Cyril Grouin; Pierre Zweigenbaum; Bruno Falissard
Journal:  Int J Methods Psychiatr Res       Date:  2015-07-17       Impact factor: 4.035

Review 4.  Language as a Window Into the Altered State of Consciousness Elicited by Psychedelic Drugs.

Authors:  Enzo Tagliazucchi
Journal:  Front Pharmacol       Date:  2022-03-22       Impact factor: 5.810

5.  Cohort profile of the South London and Maudsley NHS Foundation Trust Biomedical Research Centre (SLaM BRC) Case Register: current status and recent enhancement of an Electronic Mental Health Record-derived data resource.

Authors:  Gayan Perera; Matthew Broadbent; Felicity Callard; Chin-Kuo Chang; Johnny Downs; Rina Dutta; Andrea Fernandes; Richard D Hayes; Max Henderson; Richard Jackson; Amelia Jewell; Giouliana Kadra; Ryan Little; Megan Pritchard; Hitesh Shetty; Alex Tulloch; Robert Stewart
Journal:  BMJ Open       Date:  2016-03-01       Impact factor: 2.692
  5 in total

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