Many studies have used Digital Phenoty** of Mental Health (DPMH) to complement
classic methods of mental health assessment and monitoring. This research area proposes …

Digital biomarkers that remotely monitor symptoms have the potential to revolutionize
outcome assessments in future disease-modifying trials in Parkinson's disease (PD), by …

Background In this modern era, depression is one of the most prevalent mental disorders
from which millions of individuals are affected today. The symptoms of depression are …

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 …

Recent years have seen significant advances in the sensing capabilities of smartphones,
enabling them to collect rich contextual information such as location, device usage, and …

Depression and bipolar disorder are mood disorders affecting millions of people worldwide
that can have severe impacts on one's quality of life. Our ability to detect these illnesses is …

Background Mental disorders are normally diagnosed exclusively on the basis of symptoms,
which are identified from patients' interviews and self-reported experiences. To make mental …

Mental illnesses are often undiagnosed, highlighting the need for an effective alternative to
traditional screening surveys. We propose our Early Mental Health Uncovering (EMU) …

Digital health applications using Artificial Intelligence (AI) are a promising opportunity to
address the widening gap between available resources and mental health needs globally …

Mental illnesses are often undiagnosed, demonstrating need for an effective unbiased
alternative to traditional screening surveys. For this we propose our Early Mental Health …