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Natural Language Processing Reveals Vulnerable Mental Health Support Groups and Heightened Health Anxiety on Reddit During COVID-19: Observational Study
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In: Journal of Medical Internet Research (2020)
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Using language processing and speech analysis for the identification of psychosis and other disorders
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In: Biol Psychiatry Cogn Neurosci Neuroimaging (2020)
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Dreaming during the Covid-19 pandemic: Computational assessment of dream reports reveals mental suffering related to fear of contagion
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In: PLoS One (2020)
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Identifying signals associated with psychiatric illness utilizing language and images posted to Facebook
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In: NPJ Schizophr (2020)
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Language as a Biomarker for Psychosis: A Natural Language Processing Approach
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In: Schizophr Res (2020)
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Natural Language Processing Reveals Vulnerable Mental Health Support Groups and Heightened Health Anxiety on Reddit During COVID-19: Observational Study
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In: J Med Internet Res (2020)
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Linguistic markers predict onset of Alzheimer's disease
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In: EClinicalMedicine (2020)
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Detection of acute 3,4-methylenedioxymethamphetamine (MDMA) effects across protocols using automated natural language processing
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From discourse to pathology: Automatic identification of Parkinson’s disease patients via morphological measures across three languages
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Eyigoz, Elif; Courson, Melody; Sedeño, Lucas; Rogg, Katharina; Orozco-Arroyave, Juan Rafael; Nöth, Elmar; Skodda, Sabine; Trujillo, Natalia; Rodríguez, Mabel; Rusz, Jan; Muñoz, Edinson; Cardona, Juan F.; Herrera, Eduar; Hesse, Eugenia; Ibáñez, Agustín; Cecchi, Guillermo; García, Adolfo M.
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In: Cortex (2020)
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Abstract:
Embodied cognition research on Parkinson’s disease (PD) points to disruptions of frontostriatal language functions as sensitive targets for clinical assessment. However, no existing approach has been tested for crosslinguistic validity, let alone by combining naturalistic tasks with machine-learning tools. To address these issues, we conducted the first classifier-based examination of morphological processing (a core frontostriatal function) in spontaneous monologues from PD patients across three typologically different languages. The study comprised 330 participants, encompassing speakers of Spanish (61 patients, 57 matched controls), German (88 patients, 88 matched controls), and Czech (20 patients, 16 matched controls). All subjects described the activities they perform during a regular day, and their monologues were automatically coded via morphological tagging, a computerized method that labels each word with a part-of-speech tag (e.g., noun, verb) and specific morphological tags (e.g., person, gender, number, tense). The ensuing data were subjected to machine-learning analyses to assess whether differential morphological patterns could classify between patients and controls and reflect the former’s degree of motor impairment. Results showed robust classification rates, with over 80% of patients being discriminated from controls in each language separately. Moreover, the most discriminative morphological features were associated with the patients’ motor compromise (as indicated by Pearson r correlations between predicted and collected motor impairment scores that ranged from moderate to moderate-to-strong across languages). Taken together, our results suggest that the morphological patterning, an embodied frontostriatal domain, may be distinctively affected in PD across languages and even under ecological testing conditions.
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URL: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7655620/ https://doi.org/10.1016/j.cortex.2020.08.020 http://www.ncbi.nlm.nih.gov/pubmed/32992069
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The history of writing reflects the effects of education on discourse structure: implications for literacy, orality, psychosis and the axial age
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Differential 28-Days Cyclic Modulation of Affective Intensity in Female and Male Participants via Social Media
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S19. ANALYZING NEGATIVE SYMPTOMS AND LANGUAGE IN YOUTHS AT RISK FOR PSYCHOSIS USING AUTOMATED LANGUAGE ANALYSIS
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24.2 NATURAL LANGUAGE PROCESSING STUDIES OF PSYCHOSIS AND ITS RISK STATES
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Prediction of psychosis across protocols and risk cohorts using automated language analysis
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The maturation of speech structure in psychosis is resistant to formal education
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Predicting natural language descriptions of mono-molecular odorants
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The maturation of speech structure in psychosis is resistant to formal education
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The ontogeny of discourse structure mimics the development of literature ...
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