Latest AI and machine learning research in depression for healthcare professionals.
Accurate recognition of human motion intention (HMI) is beneficial for exoskeleton robots to improve the wearing comfort level and achieve natural human-robot interaction. A classifier trained on labeled source subjects (domains) performs poorly on unlabeled target subject since the difference in individual motor characteristics. The unsupervised domain adaptation (UDA) method has become an effect...
OBJECTIVE: Machine learning algorithms can advance clinical care, including identifying mental health conditions. These algorithms are often developed without considering the perspectives of the affected populations. This study describes the process of incorporating end-user perspectives into the development and implementation planning of a prediction algorithm for new perinatal depression onset.
OBJECTIVE: Suicide remains one of the main preventable causes of death among service members and veterans. Early detection and accurate prediction are...
BACKGROUND: People with psychosis have a higher suicide risk than the general population. Natural language processing (NLP) has been used to understan...
Traditional diagnostic methods for major depressive disorder (MDD), which rely on subjective assessments, may compromise diagnostic accuracy. In contr...
OBJECTIVE: Post-stroke depression (PSD) is a common psychiatric complication following stroke, with low clinical detection rates and delayed diagnosis...
BACKGROUND: Mood disorders (MD) are closely related to suicide attempt (SA). Developing an effective prediction model for SA in MD patients could play...
Technology dependence has long been a critical public health issue, especially among young people. With the development of AI chatbots, many individua...
Major depressive disorder represents one of the most significant global health challenges of the 21st century, affecting millions of people worldwid...
BACKGROUND: For suicide in major depression disorder, it is urgent to seek for a reliable neuroimaging biomarker with interpretable links to molecular...
Social isolation and loneliness, which have been increasing in recent years strongly contribute toward suicide rates. Although social isolation and ...
Depression is a significant mental health concern, particularly in professional environments where work-related stress, financial pressure, and life...
BACKGROUND: In the context of escalating global mental health challenges, adolescent suicide has become a critical public health concern. In current c...
This study utilized data from the 2020 wave of the China Health and Retirement Longitudinal Study database, selecting 4322 participants aged 60 and ab...
Non-suicidal self-injury (NSSI) in adolescent girls is a critical predictor of subsequent depression and suicide risk, yet current tools lack both acc...
BACKGROUND: Early diagnosis and treatment of mental illnesses is hampered by the lack of reliable markers. This study used machine learning models to ...
Suicide remains a leading cause of death in Western countries, underscoring the need for new research approaches. As social media becomes central to...
BACKGROUND: Despite the high suicide rate in South Korea, older adults are reluctant to see a psychiatrist. Recently, text mining has gained popularit...
This article proposes a robust brain-inspired audio feature extractor (RBA-FE) model for depression diagnosis, using an improved hierarchical networ...
Accurate and interpretable detection of depressive language in social media is useful for early interventions of mental health conditions, and has i...