Facial image analysis for automated suicide risk detection with deep neural networks-Reference-Cited by-同舟云学术

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Facial image analysis for automated suicide risk detection with deep neural networks

Published:2024-09-03 Issue:10 Volume:57 Page:
ISSN:1573-7462
Container-title:Artificial Intelligence Review
language:en
Short-container-title:Artif Intell Rev

Author:

Rashed Amr E. Eldin,Atwa Ahmed E. Mansour,Ahmed Ali,Badawy Mahmoud,Elhosseini Mostafa A.,Bahgat Waleed M.

Funder

The Deputyship for Research & Innovation, Ministry of Education in Saudi Arabia

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s10462-024-10882-4.pdf

Reference56 articles.

1. Aldhyani THH, Alsubari SN, Alshebami AS, Alkahtani H, Ahmed ZAT (2022) Detecting and analyzing suicidal ideation on social media using deep learning and machine learning models. Int J Environ Res Public Health 19(19):12635

2. Alghowinem S, Goecke R, Wagner M, Parker G, Breakspear M (2013a) Eye movement analysis for depression detection. In: 2013 IEEE international conference on image processing, pp 4220–4224. IEEE

3. Alghowinem S, Goecke R, Wagner M, Parkerx G, Breakspear M (2013b) Head pose and movement analysis as an indicator of depression. In: 2013 Humaine association conference on affective computing and intelligent interaction, pp 283–288. IEEE

4. Baghdadi NA, Malki A, Balaha HM, AbdulAzeem Y, Badawy M, Elhosseini M (2022) An optimized deep learning approach for suicide detection through arabic tweets. PeerJ Comput Sci 8:e1070

5. Bernert RA, Hom MA, Roberts LW (2014) A review of multidisciplinary clinical practice guidelines in suicide prevention: toward an emerging standard in suicide risk assessment and management, training and practice. Acad Psychiatry 38:585–592

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