Abstract Purpose of Review Artificial intelligence (AI) technology holds both great promise to
transform mental healthcare and potential pitfalls. This article provides an overview of AI and …

BackgroundThis paper aims to synthesise the literature on machine learning (ML) and big
data applications for mental health, highlighting current research and applications in …

Background Machine learning systems are part of the field of artificial intelligence that
automatically learn models from data to make better decisions. Natural language processing …

Suicide is a leading cause of death that defies prediction and challenges prevention efforts
worldwide. Artificial intelligence (AI) and machine learning (ML) have emerged as a means …

Depression is a leading cause of mental ill health, which has been found to increase risk of
early death. Moreover it is a major cause of suicidal ideation and leads to significant …

Background Machine learning techniques offer promise to improve suicide risk prediction. In
the current systematic review, we aimed to review the existing literature on the application of …

Abstract Language is a potential source of predictors for suicidal thoughts and behaviors
(STBs), as changes in speech characteristics, communication habits, and word choice may …

Objective: Suicide is a growing public health concern with a global prevalence of
approximately 800,000 deaths per year. The current process of evaluating suicide risk is …

Effective implementation of artificial intelligence in behavioral healthcare delivery depends
on overcoming challenges that are pronounced in this domain. Self and social stigma …

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 …