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| Verfasst von: | Chavanne, Alice V. [VerfasserIn]  |
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| | Paillère Martinot, Marie Laure [VerfasserIn] |
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| | Penttilä, Jani [VerfasserIn] |
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| | Grimmer, Yvonne [VerfasserIn] |
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| | Conrod, Patricia [VerfasserIn] |
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| | Stringaris, Argyris [VerfasserIn] |
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| | van Noort, Betteke [VerfasserIn] |
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| | Isensee, Corinna [VerfasserIn] |
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| | Becker, Andreas [VerfasserIn] |
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| | Banaschewski, Tobias [VerfasserIn] |
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| | Bokde, Arun L. W. [VerfasserIn] |
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| | Desrivières, Sylvane [VerfasserIn] |
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| | Flor, Herta [VerfasserIn] |
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| | Grigis, Antoine [VerfasserIn] |
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| | Garavan, Hugh [VerfasserIn] |
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| | Gowland, Penny [VerfasserIn] |
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| | Heinz, Andreas [VerfasserIn] |
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| | Brühl, Rüdiger [VerfasserIn] |
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| | Nees, Frauke [VerfasserIn] |
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| | Papadopoulos Orfanos, Dimitri [VerfasserIn] |
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| | Paus, Tomáš [VerfasserIn] |
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| | Poustka, Luise [VerfasserIn] |
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| | Hohmann, Sarah [VerfasserIn] |
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| | Millenet, Sabina [VerfasserIn] |
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| | Fröhner, Juliane [VerfasserIn] |
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| | Smolka, Michael [VerfasserIn] |
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| | Walter, Henrik [VerfasserIn] |
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| | Whelan, Robert [VerfasserIn] |
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| | Schumann, Gunter [VerfasserIn] |
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| | Martinot, Jean-Luc [VerfasserIn] |
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| | Artiges, Eric [VerfasserIn] |
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| Titel: | Anxiety onset in adolescents |
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| Titelzusatz: | a machine-learning prediction |
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| Verf.angabe: | Alice V. Chavanne, Marie Laure Paillère Martinot, Jani Penttilä, Yvonne Grimmer, Patricia Conrod, Argyris Stringaris, Betteke van Noort, Corinna Isensee, Andreas Becker, Tobias Banaschewski, Arun L.W. Bokde, Sylvane Desrivières, Herta Flor, Antoine Grigis, Hugh Garavan, Penny Gowland, Andreas Heinz, Rüdiger Brühl, Frauke Nees, Dimitri Papadopoulos Orfanos, Tomáš Paus, Luise Poustka, Sarah Hohmann, Sabina Millenet, Juliane H. Fröhner, Michael N. Smolka, Henrik Walter, Robert Whelan, Gunter Schumann, Jean-Luc Martinot, Eric Artiges, for the IMAGEN consortium |
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| Jahr: | 2023 |
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| Umfang: | 8 S. |
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| Fussnoten: | IMAGEN CONSORTIUM: Eric Artiges, Semiha Aydin, Christine Bach, Tobias Banaschewski, Alexis Barbot, Gareth Barker, Arun Bokde, Nadège Bordas, Zuleima Bricaud, Uli Bromberg, Ruediger Bruehl, Christian Büchel, Anna Cattrell, Patricia Conrod, Sylvane Desrivieres, Tahmine Fadai, Irina Filippi, Herta Flor, Vincent Frouin, André Galinowski, Jürgen Gallinat, Hugh Garavan, Fanny Gollier Briand, Chantal Gourlan, Penny Gowland, Stella Guldner, Andreas Heinz, Bernd Ittermann, Tianye Jia, Hervé Lemaitre, Jean-Luc Martinot, Jessica Massicotte, Ruben Miranda, Kathrin Müller, Frauke Nees, Charlotte Nymberg, Marie Laure Paillère Martinot, Tomas Paus, Zdenka Pausova, Jean-Baptiste Poline, Luise Poustka, Jan Reuter, John Rogers, Barbara Ruggeri, Anna S. Sarvasmaa, Christine Schmäl, Gunter Schumann, Maren Struve, Michael Smolka, Wolfgang Sommer, Hélène Vulser, Henrik Walter and Robert Whelan ; Online veröffentlicht: 08. Dezember 2022 ; Gesehen am 17.06.2024 |
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| Titel Quelle: | Enthalten in: Molecular psychiatry |
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| Ort Quelle: | [London] : Springer Nature, 1997 |
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| Jahr Quelle: | 2023 |
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| Band/Heft Quelle: | 28(2023), 2, Seite 639-646 |
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| ISSN Quelle: | 1476-5578 |
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| Abstract: | Recent longitudinal studies in youth have reported MRI correlates of prospective anxiety symptoms during adolescence, a vulnerable period for the onset of anxiety disorders. However, their predictive value has not been established. Individual prediction through machine-learning algorithms might help bridge the gap to clinical relevance. A voting classifier with Random Forest, Support Vector Machine and Logistic Regression algorithms was used to evaluate the predictive pertinence of gray matter volumes of interest and psychometric scores in the detection of prospective clinical anxiety. Participants with clinical anxiety at age 18-23 (N = 156) were investigated at age 14 along with healthy controls (N = 424). Shapley values were extracted for in-depth interpretation of feature importance. Prospective prediction of pooled anxiety disorders relied mostly on psychometric features and achieved moderate performance (area under the receiver operating curve = 0.68), while generalized anxiety disorder (GAD) prediction achieved similar performance. MRI regional volumes did not improve the prediction performance of prospective pooled anxiety disorders with respect to psychometric features alone, but they improved the prediction performance of GAD, with the caudate and pallidum volumes being among the most contributing features. To conclude, in non-anxious 14 year old adolescents, future clinical anxiety onset 4-8 years later could be individually predicted. Psychometric features such as neuroticism, hopelessness and emotional symptoms were the main contributors to pooled anxiety disorders prediction. Neuroanatomical data, such as caudate and pallidum volume, proved valuable for GAD and should be included in prospective clinical anxiety prediction in adolescents. |
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| DOI: | doi:10.1038/s41380-022-01840-z |
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| URL: | Bitte beachten Sie: Dies ist ein Bibliographieeintrag. Ein Volltextzugriff für Mitglieder der Universität besteht hier nur, falls für die entsprechende Zeitschrift/den entsprechenden Sammelband ein Abonnement besteht oder es sich um einen OpenAccess-Titel handelt.
kostenfrei: Volltext: https://doi.org/10.1038/s41380-022-01840-z |
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| | kostenfrei: Volltext: http://www.nature.com/articles/s41380-022-01840-z |
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| | DOI: https://doi.org/10.1038/s41380-022-01840-z |
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| Datenträger: | Online-Ressource |
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| Sprache: | eng |
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| Sach-SW: | Predictive markers |
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| | Psychiatric disorders |
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| K10plus-PPN: | 1891370731 |
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| Verknüpfungen: | → Zeitschrift |
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Anxiety onset in adolescents / Chavanne, Alice V. [VerfasserIn]; 2023 (Online-Ressource)
