This paper is in the following e-collection/theme issue:

Theme Issue 2021: Health Natural Language Processing and Applications (16) Depression and Mood Disorders; Suicide Prevention (1132) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1399) Natural Language Processing (535) Infodemiology and Infoveillance (1124)

Published on in Vol 9 , No 7 (2021) :July

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/28227, first published .
Multifeature Fusion Attention Network for Suicide Risk Assessment Based on Social Media: Algorithm Development and Validation

Multifeature Fusion Attention Network for Suicide Risk Assessment Based on Social Media: Algorithm Development and Validation

Multifeature Fusion Attention Network for Suicide Risk Assessment Based on Social Media: Algorithm Development and Validation

Authors of this article:

Jiacheng Li 1 Author Orcid Image ;   Shaowu Zhang 1 Author Orcid Image ;   Yijia Zhang 1 Author Orcid Image ;   Hongfei Lin 1 Author Orcid Image ;   Jian Wang 1 Author Orcid Image
Article Authors Cited by (3) Tweetations (3) Metrics

Journals

  1. Homan S, Gabi M, Klee N, Bachmann S, Moser A, Duri' M, Michel S, Bertram A, Maatz A, Seiler G, Stark E, Kleim B. Linguistic features of suicidal thoughts and behaviors: A systematic review. Clinical Psychology Review 2022;95:102161 View
  2. Priyamvada B, Singhal S, Nayyar A, Jain R, Goel P, Rani M, Srivastava M. Stacked CNN - LSTM approach for prediction of suicidal ideation on social media. Multimedia Tools and Applications 2023 View