For years, the scientific community has researched monitoring approaches for the detection
of certain mental disorders and risky behaviors, like depression, eating disorders, gambling …

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 …

Behavioral dysregulation that may manifest as the use of maladaptive behaviors aimed at
regulating or avoiding distress, despite potential negative health consequences, is central to …

We aimed to develop prediction models for depression among US adults with hypertension
using various machine learning (ML) approaches. Moreover, we analyzed the mechanisms …

While blockchain technology (BT) is considered secure, there are several vulnerabilities that
can breach its security. The study in artificial intelligence (AI) and BT is widely popular due to …

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 …

Adolescent suicide attempts are on the rise, presenting a significant public health concern.
Recent research aimed at improving risk assessment for adolescent suicide attempts has …

Suicide is a major global public health concern, and the application of artificial intelligence
(AI) methods, such as natural language processing (NLP), machine learning (ML), and deep …

Background Anxiety and depression are the most prevalent comorbidities among epilepsy
patients. The screen and diagnosis of anxiety and depression are quite important for the …

Background: Suicide poses a significant health burden worldwide. In many cases, people at
risk of suicide do not engage with their doctor or community due to concerns about …