Suicidal behaviour prediction models using machine learning techniques: A systematic review
Background Early detection and prediction of suicidal behaviour are key factors in suicide
control. In conjunction with recent advances in the field of artificial intelligence, there is …
control. In conjunction with recent advances in the field of artificial intelligence, there is …
Machine learning and the prediction of suicide in psychiatric populations: a systematic review
Abstract Machine learning (ML) has emerged as a promising tool to enhance suicidal
prediction. However, as many large-sample studies mixed psychiatric and non-psychiatric …
prediction. However, as many large-sample studies mixed psychiatric and non-psychiatric …
Quantifying the interrelationships between physical, social, and cognitive-emotional components of mental fitness using digital technology
Mental fitness is a construct that goes beyond a simple focus on subjective emotional
wellbeing to encompass more broadly our ability to think, feel, and act to achieve what we …
wellbeing to encompass more broadly our ability to think, feel, and act to achieve what we …
[PDF][PDF] RETRACTED: PSCNN: PatchShuffle Convolutional Neural Network for COVID-19 Explainable Diagnosis
SH Wang, Z Zhu, YD Zhang - Frontiers in public health, 2021 - frontiersin.org
Objective: COVID-19 is a sort of infectious disease caused by a new strain of coronavirus.
This study aims to develop a more accurate COVID-19 diagnosis system. Methods: First, the …
This study aims to develop a more accurate COVID-19 diagnosis system. Methods: First, the …
Predictive modelling of deliberate self-harm and suicide attempts in young people accessing primary care: a machine learning analysis of a longitudinal study
Purpose Machine learning (ML) has shown promise in modelling future self-harm but is yet
to be applied to key questions facing clinical services. In a cohort of young people accessing …
to be applied to key questions facing clinical services. In a cohort of young people accessing …
Clinical staging and the differential risks for clinical and functional outcomes in young people presenting for youth mental health care
Background Clinical staging proposes that youth-onset mental disorders develop
progressively, and that active treatment of earlier stages should prevent progression to more …
progressively, and that active treatment of earlier stages should prevent progression to more …
[HTML][HTML] A Digital Approach for Addressing Suicidal Ideation and Behaviors in Youth Mental Health Services: Observational Study
Background Long wait times for mental health treatments may cause delays in early
detection and management of suicidal ideation and behaviors, which are crucial for effective …
detection and management of suicidal ideation and behaviors, which are crucial for effective …
The temporal dependencies between social, emotional and physical health factors in young people receiving mental healthcare: a dynamic Bayesian network …
AimsThe needs of young people attending mental healthcare can be complex and often
span multiple domains (eg, social, emotional and physical health factors). These factors …
span multiple domains (eg, social, emotional and physical health factors). These factors …
[HTML][HTML] Assessment of machine learning algorithms in national data to classify the risk of self-harm among young adults in hospital: a retrospective study
Background Self-harm is one of the most common presentations at accident and emergency
departments in the UK and is a strong predictor of suicide risk. The UK Government has …
departments in the UK and is a strong predictor of suicide risk. The UK Government has …
Dynamic learning of individual-level suicidal ideation trajectories to enhance mental health care
There has recently been an increase in ongoing patient-report routine outcome monitoring
for individuals within clinical care, which has corresponded to increased longitudinal …
for individuals within clinical care, which has corresponded to increased longitudinal …