Detection of suicide risk is a highly prioritized, yet complicated task. Five decades of research have produced predictions slightly better than chance (AUCs = 0.56-0.58). In this study, Artificial Neural Network (ANN) models were constructed to pred...
OBJECTIVE: Digital media conversations can provide important insight into the concerns and struggles of people with epilepsy (PWE) outside of formal clinical settings and help generate useful information for treatment planning. Our study aimed to exp...
The journal of the American Academy of Psychiatry and the Law
Nov 21, 2019
In March 2015, a co-pilot flying Germanwings Flight 9525 deliberately pointed his airplane into a descent, killing himself, five other crew members, and 144 passengers. Subsequent investigation and review teams examined the incident and considered po...
European psychiatry : the journal of the Association of European Psychiatrists
Sep 7, 2019
Methods of suicide have received considerable attention in suicide research. The common approach to differentiate methods of suicide is the classification into "violent" versus "non-violent" method. Interestingly, since the proposition of this dichot...
BACKGROUND: Suicide is a leading cause of death worldwide. With the increasing volume of administrative health care data, there is an opportunity to evaluate whether machine learning models can improve upon statistical models for quantifying suicide ...
OBJECTIVE: Suicide in adolescents is a major problem worldwide and previous history of suicide ideation and attempt represents the strongest predictors of future suicidal behavior. The aim of this study was to develop prediction model to identify Kor...
IEEE journal of biomedical and health informatics
May 27, 2019
This paper presents a novel method for predicting suicidal ideation from electronic health records (EHR) and ecological momentary assessment (EMA) data using deep sequential models. Both EHR longitudinal data and EMA question forms are defined by asy...
BACKGROUND: Identification of individuals at increased risk for suicide is an important public health priority, but the extent to which considering clinical phenomenology improves prediction of longer term outcomes remains understudied. Hospital disc...
For decades, our ability to predict suicide has remained at near-chance levels. Machine learning has recently emerged as a promising tool for advancing suicide science, particularly in the domain of suicide prediction. The present review provides an ...
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