Computational methods for the identification of suicidal ideation: a systematic review

Limitations in the evidence include the lack of linguistic and cultural diversity and the predominance of data from social networks. These results indicate that computational techniques have high potential to support early prevention strategies for suicidal ideation. However, expanding the diversity of linguistic contexts and improving understanding of the models among non-experts, such as physicians and other interested individuals, is necessary.

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Publication Details

Journal
Frontiers in Artificial Intelligence
Published
2026-01-22
DOI
https://doi.org/10.3389/frai.2026.1704818
Primary Topic
Mental Health via Writing
Type
article
Field-Weighted Citation Impact
0.00
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article

Computational methods for the identification of suicidal ideation: a systematic review

Juan Carlos Blandón Andrade, Alejandro Morales-Ríos, Brahian Stiven Gil Arias, Grigori Sidorov
Frontiers in Artificial Intelligence
Mental Health via Writing
article

Computational methods for the identification of suicidal ideation: a systematic review

Juan Carlos Blandón Andrade, Alejandro Morales-Ríos, Brahian Stiven Gil Arias, Grigori Sidorov
article en

Abstract

Limitations in the evidence include the lack of linguistic and cultural diversity and the predominance of data from social networks. These results indicate that computational techniques have high potential to support early prevention strategies for suicidal ideation. However, expanding the diversity of linguistic contexts and improving understanding of the models among non-experts, such as physicians and other interested individuals, is necessary.

Frontiers in Artificial IntelligenceVol. 9
Technological University of Pereira (CO), Universidad Católica de Pereira (CO), Instituto Politécnico Nacional (MX)
Reduced inequalities
Openalex Percentile: Top 85%
Mental Health via Writing
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