The steps that young people and suicide prevention professionals think the social media industry and policymakers should take to improve online safety. A nested …

J Robinson, P Thorn, S McKay, H Richards… - Frontiers in Child and …, 2023 - frontiersin.org
Introduction Concerns exist about the relationship between social media and youth self-
harm and suicide. Study aims were to examine the extent to which young people and …

A machine-learning model to predict suicide risk in Japan based on national survey data

PH Chou, SC Wang, CS Wu, M Horikoshi… - Frontiers in psychiatry, 2022 - frontiersin.org
Objective Several prognostic models of suicide risk have been published; however, few
have been implemented in Japan using longitudinal cohort data. The aim of this study was …

A systematic review and future perspective of mental illness detection using artificial intelligence on multimodal digital media

U Ananthanagu, P Agarwal - … Systems: Selected Papers of WorldS4 2022 …, 2023 - Springer
In recent couple of years, social media platform has attained a tremendous growth in sharing
information and become an integral part of everyday life. Such real-time information portrays …

[PDF][PDF] Quantifying suicidal ideation on social media using machine learning: a critical review

ST Rabani, QR Khan, AMUD Khanday - Iraqi Journal of Science, 2021 - iasj.net
Suicidal ideation is one of the severe mental health issues and a serious social problem
faced by our society. This problem has been usually dealt with through the psychological …

Identifying suicide ideation in mental health application posts: A random forest algorithm

H Moradian, MA Lau, A Miki, ED Klonsky… - Death …, 2023 - Taylor & Francis
The growing use of digitized mental health applications requires new reliable early
screening tools to identify user suicide risk. We used a lexicon-based random forest …

[HTML][HTML] Applying the health belief model to characterize racial/ethnic differences in digital conversations related to depression pre-and mid-COVID-19: Descriptive …

R Castilla-Puentes, J Pesa, C Brethenoux… - JMIR Formative …, 2022 - formative.jmir.org
Background The prevalence of depression in the United States is> 3 times higher mid-
COVID-19 versus prepandemic. Racial/ethnic differences in mindsets around depression …

Neural activity during inhibitory control predicts suicidal ideation with machine learning

J Nan, G Grennan, S Ravichandran… - … —Digital Psychiatry and …, 2024 - nature.com
Suicide is a leading cause of death in the US and worldwide. Current strategies for
preventing suicide are often focused on the identification and treatment of risk factors …

[PDF][PDF] Predicting the utilization of mental health treatment with various machine learning algorithms

M Sharma, S Mahapatra, A Shankar, X Wang - Mental Health, 2021 - academia.edu
In 2017, about 792 million people (more than 10% of the global population) lived their lives
with a mental disorder [24]–78 million of which committed suicide because of it. In these …

Machine learning based psychotic behaviors prediction from Facebook status updates

M Ali, A Baqir, HHR Sherazi, A Hussain… - Computers, Materials …, 2022 - eprints.gla.ac.uk
With the advent of technological advancements and the widespread Internet connectivity
during the last couple of decades, social media platforms (such as Facebook, Twitter, and …

Explainability, public reason, and medical artificial intelligence

M Da Silva - Ethical Theory and Moral Practice, 2023 - Springer
The contention that medical artificial intelligence (AI) should be 'explainable'is widespread in
contemporary philosophy and in legal and best practice documents. Yet critics argue that …