Cargando…

Suicide risk detection using artificial intelligence: the promise of creating a benchmark dataset for research on the detection of suicide risk

Suicide is a leading cause of death that demands cross-disciplinary research efforts to develop and deploy suicide risk screening tools. Such tools, partly informed by influential suicide theories, can help identify individuals at the greatest risk of suicide and should be able to predict the transi...

Descripción completa

Detalles Bibliográficos
Autores principales: Parsapoor (Mah Parsa), Mahboobeh, Koudys, Jacob W., Ruocco, Anthony C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10411603/
https://www.ncbi.nlm.nih.gov/pubmed/37564247
http://dx.doi.org/10.3389/fpsyt.2023.1186569
_version_ 1785086700991545344
author Parsapoor (Mah Parsa), Mahboobeh
Koudys, Jacob W.
Ruocco, Anthony C.
author_facet Parsapoor (Mah Parsa), Mahboobeh
Koudys, Jacob W.
Ruocco, Anthony C.
author_sort Parsapoor (Mah Parsa), Mahboobeh
collection PubMed
description Suicide is a leading cause of death that demands cross-disciplinary research efforts to develop and deploy suicide risk screening tools. Such tools, partly informed by influential suicide theories, can help identify individuals at the greatest risk of suicide and should be able to predict the transition from suicidal thoughts to suicide attempts. Advances in artificial intelligence have revolutionized the development of suicide screening tools and suicide risk detection systems. Thus, various types of AI systems, including text-based systems, have been proposed to identify individuals at risk of suicide. Although these systems have shown acceptable performance, most of them have not incorporated suicide theories in their design. Furthermore, directly applying suicide theories may be difficult because of the diversity and complexity of these theories. To address these challenges, we propose an approach to develop speech- and language-based suicide risk detection systems. We highlight the promise of establishing a benchmark textual and vocal dataset using a standardized speech and language assessment procedure, and research designs that distinguish between the risk factors for suicide attempt above and beyond those for suicidal ideation alone. The benchmark dataset could be used to develop trustworthy machine learning or deep learning-based suicide risk detection systems, ultimately constructing a foundation for vocal and textual-based suicide risk detection systems.
format Online
Article
Text
id pubmed-10411603
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher Frontiers Media S.A.
record_format MEDLINE/PubMed
spelling pubmed-104116032023-08-10 Suicide risk detection using artificial intelligence: the promise of creating a benchmark dataset for research on the detection of suicide risk Parsapoor (Mah Parsa), Mahboobeh Koudys, Jacob W. Ruocco, Anthony C. Front Psychiatry Psychiatry Suicide is a leading cause of death that demands cross-disciplinary research efforts to develop and deploy suicide risk screening tools. Such tools, partly informed by influential suicide theories, can help identify individuals at the greatest risk of suicide and should be able to predict the transition from suicidal thoughts to suicide attempts. Advances in artificial intelligence have revolutionized the development of suicide screening tools and suicide risk detection systems. Thus, various types of AI systems, including text-based systems, have been proposed to identify individuals at risk of suicide. Although these systems have shown acceptable performance, most of them have not incorporated suicide theories in their design. Furthermore, directly applying suicide theories may be difficult because of the diversity and complexity of these theories. To address these challenges, we propose an approach to develop speech- and language-based suicide risk detection systems. We highlight the promise of establishing a benchmark textual and vocal dataset using a standardized speech and language assessment procedure, and research designs that distinguish between the risk factors for suicide attempt above and beyond those for suicidal ideation alone. The benchmark dataset could be used to develop trustworthy machine learning or deep learning-based suicide risk detection systems, ultimately constructing a foundation for vocal and textual-based suicide risk detection systems. Frontiers Media S.A. 2023-07-24 /pmc/articles/PMC10411603/ /pubmed/37564247 http://dx.doi.org/10.3389/fpsyt.2023.1186569 Text en Copyright © 2023 Parsapoor (Mah Parsa), Koudys and Ruocco. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Psychiatry
Parsapoor (Mah Parsa), Mahboobeh
Koudys, Jacob W.
Ruocco, Anthony C.
Suicide risk detection using artificial intelligence: the promise of creating a benchmark dataset for research on the detection of suicide risk
title Suicide risk detection using artificial intelligence: the promise of creating a benchmark dataset for research on the detection of suicide risk
title_full Suicide risk detection using artificial intelligence: the promise of creating a benchmark dataset for research on the detection of suicide risk
title_fullStr Suicide risk detection using artificial intelligence: the promise of creating a benchmark dataset for research on the detection of suicide risk
title_full_unstemmed Suicide risk detection using artificial intelligence: the promise of creating a benchmark dataset for research on the detection of suicide risk
title_short Suicide risk detection using artificial intelligence: the promise of creating a benchmark dataset for research on the detection of suicide risk
title_sort suicide risk detection using artificial intelligence: the promise of creating a benchmark dataset for research on the detection of suicide risk
topic Psychiatry
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10411603/
https://www.ncbi.nlm.nih.gov/pubmed/37564247
http://dx.doi.org/10.3389/fpsyt.2023.1186569
work_keys_str_mv AT parsapoormahparsamahboobeh suicideriskdetectionusingartificialintelligencethepromiseofcreatingabenchmarkdatasetforresearchonthedetectionofsuiciderisk
AT koudysjacobw suicideriskdetectionusingartificialintelligencethepromiseofcreatingabenchmarkdatasetforresearchonthedetectionofsuiciderisk
AT ruoccoanthonyc suicideriskdetectionusingartificialintelligencethepromiseofcreatingabenchmarkdatasetforresearchonthedetectionofsuiciderisk