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

Abstract

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.

Exploring the Role of First-Person Singular Pronouns in Detecting Suicidal Ideation: A Machine Learning Analysis of Clinical Transcripts

“…Recent advancements in artificial intelligence have led to the development of suicide detection systems that utilize machine learning (ML) and natural language processing (NLP) algorithms [20][21][22]. These algorithms analyze textual data from various sources, including social media platforms [23], electronic health records [24], suicide notes [4], and counseling transcripts [25].…”

The Role of Artificial Intelligence in Mental Health: A Review

“…Furthermore, AI can assume a crucial role in the realm of suicide prevention, which is an essential component of mental health. By conducting a comprehensive examination of data derived from many sources, including social media posts, phone calls, and online chat logs, AI systems possess the capability to detect individuals who may be susceptible to suicide (5). The timely identification of persons at high risk allows healthcare practitioners to take proactive measures, including timely support and interventions.…”