Study Results from University of Oum El Bouaghi Broaden Understanding of Anxiety Disorders (A Multi-Class Deep Learning Approach for Early Detection of Depressive and Anxiety Disorders Using Twitter Data).
In: Mental Health Weekly Digest, 2023-12-15, S. 778
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Zugriff:
A recent study conducted by researchers at the University of Oum El Bouaghi in Algeria explores the use of social media data, specifically Twitter, for the early detection of depressive and anxiety disorders. The researchers propose a methodology that involves deep learning techniques to develop effective multi-class models for detecting both depression and anxiety disorders. The study compares the results obtained from these models with other binary classification models and concludes that the multi-class models are satisfactory and competitive. This research provides valuable insights into the potential of social media data for mental health detection and highlights the importance of considering multiple mental disorders simultaneously. [Extracted from the article]
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Study Results from University of Oum El Bouaghi Broaden Understanding of Anxiety Disorders (A Multi-Class Deep Learning Approach for Early Detection of Depressive and Anxiety Disorders Using Twitter Data).
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Zeitschrift: | Mental Health Weekly Digest, 2023-12-15, S. 778 |
Veröffentlichung: | 2023 |
Medientyp: | serialPeriodical |
ISSN: | 1543-6616 (print) |
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