MHA: a multimodal hierarchical attention model for depression detection in social media.

Li, Zepeng; An, Zhengyi; Cheng, Wenchuan; Zhou, Jiawei; Zheng, Fang; Hu, Bin

Li, Zepeng; An, Zhengyi; Cheng, Wenchuan; Zhou, Jiawei; Zheng, Fang; Hu, Bin.

Afiliação

Li Z; Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and Engineering, Lanzhou University, Lanzhou, 730000 Gansu China.
An Z; Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and Engineering, Lanzhou University, Lanzhou, 730000 Gansu China.
Cheng W; Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and Engineering, Lanzhou University, Lanzhou, 730000 Gansu China.
Zhou J; Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and Engineering, Lanzhou University, Lanzhou, 730000 Gansu China.
Zheng F; Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and Engineering, Lanzhou University, Lanzhou, 730000 Gansu China.
Hu B; Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and Engineering, Lanzhou University, Lanzhou, 730000 Gansu China.

Health Inf Sci Syst ; 11(1): 6, 2023 Dec.

Article em En | MEDLINE | ID: mdl-36660408

Palavras-chave

Attention mechanism; Deep neural network; Depression detection; Multimodality; Social media

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies Idioma: En Revista: Health Inf Sci Syst Ano de publicação: 2023 Tipo de documento: Article

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