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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Page: 1 2 Hits 1 – 20 of 26 1 Neural Topic Modeling of Psychotherapy Sessions ... Lin, Baihan; Bouneffouf, Djallel; Cecchi, Guillermo. - : arXiv, 2022 BASE Show details 2 Natural Language Processing Reveals Vulnerable Mental Health Support Groups and Heightened Health Anxiety on Reddit During COVID-19: Observational Study Low, Daniel M.; Rumker, Laurie; Talkar, Tanya... In: Journal of Medical Internet Research (2020) BASE Show details 3 Using language processing and speech analysis for the identification of psychosis and other disorders Corcoran, Cheryl Mary; Cecchi, Guillermo In: Biol Psychiatry Cogn Neurosci Neuroimaging (2020) BASE Show details 4 Dreaming during the Covid-19 pandemic: Computational assessment of dream reports reveals mental suffering related to fear of contagion Mota, Natália Bezerra; Weissheimer, Janaina; Ribeiro, Marina... In: PLoS One (2020) BASE Show details 5 Identifying signals associated with psychiatric illness utilizing language and images posted to Facebook Birnbaum, Michael L.; Norel, Raquel; Van Meter, Anna... In: NPJ Schizophr (2020) BASE Show details 6 Language as a Biomarker for Psychosis: A Natural Language Processing Approach Corcoran, Cheryl M.; Mittal, Vijay A.; Bearden, Carrie E.... In: Schizophr Res (2020) BASE Show details 7 Natural Language Processing Reveals Vulnerable Mental Health Support Groups and Heightened Health Anxiety on Reddit During COVID-19: Observational Study Low, Daniel M; Rumker, Laurie; Talkar, Tanya... In: J Med Internet Res (2020) BASE Show details 8 Linguistic markers predict onset of Alzheimer's disease Eyigoz, Elif; Mathur, Sachin; Santamaria, Mar... In: EClinicalMedicine (2020) BASE Show details 9 Detection of acute 3,4-methylenedioxymethamphetamine (MDMA) effects across protocols using automated natural language processing Agurto, Carla; Cecchi, Guillermo A.; Norel, Raquel. - : Springer International Publishing, 2020 BASE Show details 10 From discourse to pathology: Automatic identification of Parkinson’s disease patients via morphological measures across three languages Eyigoz, Elif; Courson, Melody; Sedeño, Lucas... In: Cortex (2020) BASE Show details 11 The history of writing reflects the effects of education on discourse structure: implications for literacy, orality, psychosis and the axial age Pinheiro, Sylvia; Mota, Natália Bezerra; Sigman, Mariano. - : Elsevier, 2020 BASE Show details 12 Differential 28-Days Cyclic Modulation of Affective Intensity in Female and Male Participants via Social Media Gallino, Lucila; Carrillo, Facundo; Cecchi, Guillermo A.. - : Frontiers Media S.A., 2019 BASE Show details 13 SPEECH MARKERS FOR CLINICAL ASSESSMENT OF COCAINE USERS Agurto, Carla; Norel, Raquel; Pietrowicz, Mary. - 2019 BASE Show details 14 S19. ANALYZING NEGATIVE SYMPTOMS AND LANGUAGE IN YOUTHS AT RISK FOR PSYCHOSIS USING AUTOMATED LANGUAGE ANALYSIS Stanislawski, Emma; Bilgrami, Zarina; Sarac, Cansu. - : Oxford University Press, 2019 BASE Show details 15 24.2 NATURAL LANGUAGE PROCESSING STUDIES OF PSYCHOSIS AND ITS RISK STATES Cecchi, Guillermo; Gutierrez, Elkin; Corcoran, Cheryl. - : Oxford University Press, 2019 Abstract: BACKGROUND: Subtle disturbance in language production is evident in schizophrenia across illness stages. Recently, we have shown that reductions in semantic coherence and syntactic complexity are evident in schizophrenia prior to initial psychosis onset, and cross-validated a machine learning linguistic classifier/predictor of later psychosis onset in two independent clinical high risk (CHR) cohorts. In the current study, we turn our attention to the use of idiosyncratic speech and metaphor in spoken language in both schizophrenia patients and clinical high-risk youths, which can be considered to be a feature of semantic incoherence at the single word level (Kuperberg et al., 2010). Canonical examples from Andreasen (1986) include “time vessel” for “watch” and “hand shoe” for “glove”. Manual analyses have suggested increased use of idiosyncratic/bizarre metaphors among schizophrenia patients, as compared with controls (Billow et al., 1997). Herein, we used automated natural language processing to assess idiosyncratic speech in schizophrenia and its risk states. METHODS: Transcripts of open-ended interviews (Ben-David et al., 2014) were obtained from 18 patients with schizophrenia, 15 healthy controls, and 34 youths at clinical high risk (CHR) for psychosis, of whom five were known to develop psychosis within 2.5 years, previously assessed for semantic coherence and syntactic complexity (Bedi et al., 2015). Metaphors were tagged as tokens in running text, using a metaphor detection algorithm (Do Dinh and Gurevych) that was trained on the VU Amsterdam Metaphor Corpus (Steen et al., 2010), using supervised sequential learning on a multilayer perceptron (1 hidden layer) with a sliding window (100 epochs). Each token was rated on sentiment and bizarreness of words was measured (measuring likelihood of next word in a 2-gram model). RESULTS: Schizophrenia patients had a significantly higher proportion of metaphor tokens in speech, as compared with healthy comparison subjects (6.3% vs. 5.2%, t = 3.76, p < .001); there were no sex differences in use of metaphor. We used leave-one-out cross-validation (LOO-CV) of metaphor, sentiment and bizarreness features, along with sex and age, to generate a support vector classifier with 84% accuracy (p <.005) in discriminating the speech of schizophrenia patients from healthy controls. We similarly used these same features to generate a convex hull classifier that had 97% accuracy in predicting psychosis in the CHR group. Finally, we applied the schizophrenia metaphor/sentiment/bizarreness classifier to the CHR cohort, tagging 29 of 34 CHR patients (including all CHR converters), suggesting that the idiosyncratic use of speech seen in schizophrenia might be characteristic of spectrum disorders, independent of psychosis outcome. CONCLUSIONS: Automated linguistic analyses of schizophrenia and its risk states can be extended from semantic coherence metrics at the phrase or sentence level to the level of single words. In this first use of automated methods to detect idiosyncratic speech and metaphors in schizophrenia and its risk states, we find increased usage in schizophrenia, as compared with healthy individuals, a pattern that extends to the clinical risk state that is sensitive but not specific to psychosis outcome, suggesting it might be used as a screen to identify individuals with attenuated psychosis syndrome. Keyword: Plenary/Symposia URL: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6455632/ https://doi.org/10.1093/schbul/sbz022.097 BASE Hide details 16 Prediction of psychosis across protocols and risk cohorts using automated language analysis Corcoran, Cheryl M.; Carrillo, Facundo; Fernández‐Slezak, Diego. - : John Wiley and Sons Inc., 2018 BASE Show details 17 The maturation of speech structure in psychosis is resistant to formal education Mota, Natália Bezerra; Sigman, Mariano; Cecchi, Guillermo. - : Nature Publishing Group UK, 2018 BASE Show details 18 Predicting natural language descriptions of mono-molecular odorants Gutiérrez, E. Darío; Dhurandhar, Amit; Keller, Andreas. - : Nature Publishing Group UK, 2018 BASE Show details 19 The maturation of speech structure in psychosis is resistant to formal education Mota, Natália Bezerra; Sigman, Mariano; Cecchi, Guillermo. - 2018 BASE Show details 20 The ontogeny of discourse structure mimics the development of literature ... Mota, Natalia Bezerra; Pinheiro, Sylvia; Sigman, Mariano. - : arXiv, 2016 BASE Show details Page: 1 2

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