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

High prevalence of mental illness and the need for effective mental health care, combined
with recent advances in AI, has led to an increase in explorations of how the field of machine …

Social and medical problems associated with stress are increasing globally and seriously
affect mental health and well-being. However, an effective stress-level monitoring method is …

Establishing the diagnosis of trauma-related disorders such as Acute Stress Disorder (ASD)
and Posttraumatic Stress Disorder (PTSD) have always been a challenge in clinical practice …

Traditional regression-based approaches do not provide good results in diagnosis and
prediction of occurrences of cardiovascular diseases (CVD). Therefore, the goal of this …

Over the last decade, an increasing number of studies have focused on automated
recognition of human emotions by machines. However, performances of machine emotion …

Knowing what information a user wants is a paramount challenge to information science and
technology. Implicit feedback is key to solving this challenge, as it allows information …

The paper describes a mobile solution for the early recognition and management of stress
based on continuous monitoring of heart rate variability (HRV) and contextual data (activity …

Stress is a known contributor to several life-threatening medical conditions and a risk factor
for triggering acute cardiovascular events, as well as a root cause of several social …

The paper describes the design rationales and algorithms underlying SmartCo**, a
mobile solution for recognizing stress based on the continuous monitoring of heart rate …