Latest AI and machine learning research in depression for healthcare professionals.
Personalized data-driven interventions for depression are much needed. Here, we leveraged N-of-1 machine learning (ML) to optimally target behavioral lifestyle interventions for depression. 50 individuals with mild-to-moderate depression enrolled in the single-arm, open-label Personalized Mood Augmentation (PerMA) pilot clinical trial (NCT05662254). Participants completed a two-week digital monito...
OBJECTIVE: To explore the clinical value of AI-assisted pulmonary rehabilitation education in patients undergoing thoracoscopic surgery for lung cancer. METHODS: This was a non-randomized, two-period comparative study comparing AI-assisted education with routine education for postoperative pulmonary rehabilitation in lung cancer patients. Patients who underwent thoracoscopic radical lung cancer su...
OBJECTIVE: Suicide is a leading cause of death among youth, and adverse childhood experiences (ACEs) are established risk factors for suicidality. Thi...
Clinicians are tasked with predicting and preventing suicidal behavior among their patients; however, there is currently no method for accurately pred...
OBJECTIVE: Family caregivers of persons with dementia experience grief as the care recipients' dementia advances. Here, we explore how various interpe...
Major depressive disorder (MDD) may exhibit deficits in the inhibition of negative information. This study investigated whether there are inhibition d...
BACKGROUND: With the rapidly aging population, mental health among older adults has received growing attention. Although the likelihood of experiencin...
Major Depressive Disorder (MDD) is a highly prevalent mental health condition, and a deeper understanding of its neurocognitive foundations is essenti...
Currently, artificial intelligence (AI) is clinically relevant to mood and anxiety care, but the evidence base is uneven across use cases. This narrat...
BACKGROUND: Bullying victimization among Chinese adolescents manifests in distinct types (verbal, physical, relational, cyberbullying) with unique adv...
BACKGROUND: The sound of speech reflects the speaker's mood in a way that may enable objective measurement of depression from speech audio recordings....
In recent years, there has been a notable increase in the use of supervised detection methods of major depressive disorder (MDD) based on electroencep...
BACKGROUND: Major depressive disorder (MDD) affects approximately 1 in 6 adults during their lifetime, yet antidepressant selection relies predominant...
Psychological support hotlines provide immediate help to individuals in crisis, with operators assessing emotional states and suicide risk. However, i...
OBJECTIVE: Depressive symptoms are highly prevalent among people with eating disorders (ED). Although at the group level, depressive symptoms tend to ...
Despite the critical role of mental health services in suicide prevention, disparities in service utilization persist across various individual and so...
Ketamine has demonstrated rapid antidepressant efficacy in treatment-resistant depression (TRD), but clinical decision-making is challenging due to va...
BACKGROUND: Parkinson's disease (PD) exhibits substantial heterogeneity in clinical presentation and longitudinal progression, complicating prognosis,...
Therapeutic alliance is a core predictor of psychotherapeutic outcome, in general, and suicide prevention, specifically. Although clinical literature ...
BACKGROUND: American Indian and Alaska Native communities experience disproportionately high suicide rates. While machine learning (ML) models leverag...