Neural Network Dual Architecture for Depression Detection Using Cloud Services

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dc.contributor.authorTymofiiev, I.
dc.contributor.authorMazurets, O.
dc.contributor.authorHardysh, D.
dc.contributor.authorMolchanova, M.
dc.contributor.authorМазурець, Олександр Вікторович
dc.date.accessioned2024-12-10T18:28:46Z
dc.date.available2024-12-10T18:28:46Z
dc.date.issued2024
dc.description.abstractA method of detecting a depressive state by means of NLP was developed, which is designed to transform input data in the form of text and a trained neural network model of dual architecture into output data in the form of a numerical assessment of the presence of a depressive state. The proposed method differs from analogs in that it combines a two-stream architecture, which is based on the use of two parallel neural networks, each of which specializes in the analysis of different aspects of the text - syntactic and semantic.
dc.identifier.citationTymofiiev I., Mazurets O., Hardysh D., Molchanova M. Neural Network Dual Architecture for Depression Detection Using Cloud Services. Scientific Research in the Era of Digital Technologies: Challenges and Opportunities. Proceedings of the XLVІ International scientific and practical conference. November 6-8, 2024. Barcelona, Spain. 2024. Pp. 84-88.
dc.identifier.urihttps://elar.khmnu.edu.ua/handle/123456789/17231
dc.language.isoen
dc.titleNeural Network Dual Architecture for Depression Detection Using Cloud Services
dc.typeСтаття
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