Suicide Ideation Prediction Through Deep Learning: An Integration of CNN and Bidirectional LSTM with Word Embeddings
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-62277-9_16
Reference20 articles.
1. Ahn, S.Y., Yu, S., Kim, J.E., Song, I.H.: The relationship between suicide bereavement and suicide ideation: analysis of the mediating effect of complicated grief. J. Affect. Disord. 331, 43–49 (2023). https://doi.org/10.1016/J.JAD.2023.03.008
2. Aldhyani, T.H.H., Alsubari, S.N., Alshebami, A.S., Alkahtani, H., Ahmed, Z.A.T.: Detecting and analyzing suicidal ideation on social media using deep learning and machine learning models. Int. J. Environ. Res. Public Health 19(19), 1–16 (2022). https://doi.org/10.3390/ijerph191912635
3. Davidson, J.E., et al.: Job-Related problems prior to nurse suicide, 2003–2017: a mixed methods analysis using natural language processing and thematic analysis. J. Nurs. Regul. 12(1), 28–39 (2021). https://doi.org/10.1016/S2155-8256(21)00017-X
4. Dong, L., Kalesnikava, V.A., Gonzalez, R., Mezuk, B.: Beyond depression: estimating 12-months prevalence of passive suicidal ideation in mid- and late-life in the health and retirement study. Am. J. Geriatr. Psychiatry 27(12), 1399–1410 (2019). https://doi.org/10.1016/j.jagp.2019.06.015
5. Fartacek, C., Kunrath, S., Aichhorn, W., Plöderl, M.: Therapeutic alliance and change in suicide ideation among psychiatric inpatients at risk for suicide. J. Affect. Disord. 323, 793–798 (2023). https://doi.org/10.1016/J.JAD.2022.12.028
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