Adolescent suicidal risk assessment in clinician-patient interaction

V Venek, S Scherer, LP Morency… - IEEE Transactions on …, 2017 - ieeexplore.ieee.org
Youth suicide is a major public health problem. It is the third leading cause of death in the
United States for ages 13 through 18. Many adolescents that face suicidal thoughts or make …

Adolescent suicidal risk assessment in clinician-patient interaction: A study of verbal and acoustic behaviors

V Venek, S Scherer, LP Morency… - 2014 IEEE Spoken …, 2014 - ieeexplore.ieee.org
Suicide among adolescents is a major public health problem: it is the third leading cause of
death in the US for ages 13-18. Up to now, there is no objective ways to assess the suicidal …

Identification of imminent suicide risk among young adults using text messages

AL Nobles, JJ Glenn, K Kowsari… - Proceedings of the …, 2018 - dl.acm.org
Suicide is the second leading cause of death among young adults but the challenges of
preventing suicide are significant because the signs often seem invisible. Research has …

A controlled trial using natural language processing to examine the language of suicidal adolescents in the emergency department

JP Pestian, J Grupp‐Phelan… - Suicide and Life …, 2016 - Wiley Online Library
What adolescents say when they think about or attempt suicide influences the medical care
they receive. Mental health professionals use teenagers' words, actions, and gestures to …

A feasibility study using a machine learning suicide risk prediction model based on open-ended interview language in adolescent therapy sessions

J Cohen, J Wright-Berryman, L Rohlfs, D Wright… - International journal of …, 2020 - mdpi.com
Background: As adolescent suicide rates continue to rise, innovation in risk identification is
warranted. Machine learning can identify suicidal individuals based on their language …

Using machine learning to classify suicide attempt history among youth in medical care settings

TA Burke, R Jacobucci, BA Ammerman, LB Alloy… - Journal of affective …, 2020 - Elsevier
Background The current study aimed to classify recent and lifetime suicide attempt history
among youth presenting to medical settings using machine learning (ML) as applied to a …

[HTML][HTML] Comparing machine learning to a rule-based approach for predicting suicidal behavior among adolescents: Results from a longitudinal population-based …

CL Van Vuuren, K Van Mens, D de Beurs… - Journal of affective …, 2021 - Elsevier
Introduction Suicidal thoughts and suicide attempts are one of the most prominent public
health concerns in adolescents and therefore early detection is important to initiate …

Intensive longitudinal assessment of adolescents to predict suicidal thoughts and behaviors

RP Auerbach, R Lan, H Galfalvy, KL Alqueza… - Journal of the American …, 2023 - Elsevier
Objective Suicide is a leading cause of death among adolescents. However, there are no
clinical tools to detect proximal risk for suicide. Method Participants included 13-to 18-year …

Predicting short-term suicidal thoughts in adolescents using machine learning: developing decision tools to identify daily level risk after hospitalization

EK Czyz, HJ Koo, N Al-Dajani, CA King… - Psychological …, 2023 - cambridge.org
BackgroundMobile technology offers unique opportunities for monitoring short-term suicide
risk in daily life. In this study of suicidal adolescent inpatients, theoretically informed risk …

Machine learning for suicidal ideation identification: A systematic literature review

WF Heckler, JV de Carvalho, JLV Barbosa - Computers in Human Behavior, 2022 - Elsevier
Suicide causes approximately one death every 40 s. Suicidal ideation is the first stage in the
risk scale, being a potential gate for suicide prevention. Machine learning emerged as a …