Precise remote evaluation of both suicide risk and psychiatric disorders is critical for suicide prevention as well as for psychiatric well-being. Using questionnaires is an alternative to labor-intensive diagnostic interviews in a large general popu...
Post-traumatic stress disorder (PTSD) is characterized by complex, heterogeneous symptomology, thus detection outside traditional clinical contexts is difficult. Fortunately, advances in mobile technology, passive sensing, and analytics offer promisi...
Early identification of patients with life-threatening risks such as delirium is crucial in order to initiate preventive actions as quickly as possible. Despite intense research on machine learning for the prediction of clinical outcomes, the accepta...
Understanding the specificity of symptom change in schizophrenia can facilitate the evaluation antipsychotic efficacy for different symptom domains. Previous work identified a transform of PANSS using an uncorrelated PANSS score matrix (UPSM) to redu...
A reliable diagnosis of adult Attention Deficit/Hyperactivity Disorder (ADHD) is challenging as many of the symptoms of ADHD resemble symptoms of other disorders. ADHD is associated with gambling disorder and obesity, showing overlaps of about 20% wi...
The present study is aimed at identifying the most prominent determinants of OCD along with their strength to classify the OCD patients from healthy controls. The data for this cross-sectional study were collected from 200 diagnosed OCD patients and ...
OBJECTIVES: To investigate the effect of a social robot intervention on depression, loneliness, and quality of life of older adults in long-term care (LTC) and to explore participants' experiences and perceptions after the intervention.
BACKGROUND: Concomitant use of complementary, multimodal imaging measures and neurocognitive measures is reported to have higher accuracy as a biomarker in Alzheimer's dementia. However, such an approach has not been examined to differentiate healthy...
OBJECTIVE: People with epilepsy are at increased risk for mental health comorbidities. Machine-learning methods based on spoken language can detect suicidality in adults. This study's purpose was to use spoken words to create machine-learning classif...
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