Journal: Psychiatry investigation
Enhanced technology in computer and internet has driven scale and quality of data to be improved in various areas including healthcare sectors. Machine Learning (ML) has played a pivotal role in efficiently analyzing those big data, but a general misunderstanding of ML algorithms still exists in applying them (e.g., ML techniques can settle a problem of small sample size, or deep learning is the ML algorithm). This paper reviewed the research of diagnosing mental illness using ML algorithm and suggests how ML techniques can be employed and worked in practice.
Bipolar disorder is a severe and enduring psychiatric condition which in many cases starts during early adulthood and follows a relapsing and remitting course throughout life. In many patients the disease follows a progressive path with brief periods of inter-episode recovery, sub-threshold symptoms, treatment resistance and increasing functional impairment in the biopsychosocial domains. Knowledge about the neurobiology of bipolar disorder is increasing steadily and evidence from several lines of research implicates immuno-inflammatory mechanisms in the brain and periphery in the etiopathogenesis of this illness and its comorbidities. The main findings are an increase in the levels of proinflammatory cytokines during acute episodes with a decrease in neurotrophic support. Related to these factors are glial cell dysfunction, neuro-endocrine abnormalities and neurotransmitter aberrations which together cause plastic changes in the mood regulating areas of the brain and neuroprogression of the bipolar diathesis. Research in the above mentioned areas is providing an opportunity to discover novel biomarkers for the disease and the field is reaching a point where major breakthroughs can be expected in the not too distant future. It is hoped that with new discoveries fresh avenues will be found to better treat an otherwise recalcitrant disease.
A considerable proportion of suicide attempts are the result of sudden desires. Understanding such impulsive suicide attempts is necessary for effective interventions. We evaluated the impulsivity of suicide attempters treated in emergency rooms. The aim of the study was to identify the characteristics of impulsive suicide attempts by comparing these individuals to those who attempted to commit suicide in a non-impulsive manner.
Physical or mental imbalance caused by harmful stimuli can induce stress to maintain homeostasis. During chronic stress, the sympathetic nervous system is hyperactivated, causing physical, psychological, and behavioral abnormalities. At present, there is no accepted standard for stress evaluation. This review aimed to survey studies providing a rationale for selecting heart rate variability (HRV) as a psychological stress indicator.
Paruresis is a special type of non-generalized social phobia that involves fear and avoidance of urination in public restrooms. We administered eight 60-minute sessions of desensitization of triggers and urge reduction (DeTUR), an addiction protocol of eye movement desensitization and reprocessing (EMDR) therapy, to a 29-year old man with paruresis of 10 year duration. Because phobic avoidance is the hallmark of any anxiety disorder, we applied DeTUR targeting the urge to avoid each anxiety-provoking situation in succession. After treatment, the participant no longer met the requirements for a diagnosis of social anxiety disorder, and the self-reported symptoms of social anxiety had decreased to non-clinical levels; furthermore, these treatment gains were maintained at the one-year follow-up. Further clinical studies are needed to generalize this finding.
The present study compared cancer-related fatigue (CRF) and chronic fatigue syndrome (CFS) using multidimensional measurements with the aim of better understanding characteristics and exploring markers of two similar fatigue syndromes.
The aim of this study was to examine the concurrent validity of a newly developed computerized memory diagnostic system (MDS) with the Korean version of the Consortium to Establish a Registry for Alzheimer’s Disease Assessment Packet (CERAD-K).
The aim of the present study was to investigate differences in discontinuation time among antidepressants and total antidepressant discontinuation rate of patients with depression over a 6 month period in a naturalistic treatment setting.
Biological markers for Alzheimer’s disease (AD) will help clinicians make objective diagnoses early during the course of dementia. Previous studies have suggested that cell cycle dysregulation begins earlier than the onset of clinical manifestations in AD.
Depressive symptoms are common in Alzheimer’s disease (AD) and they might influence the course and prognosis of AD. Depression could appear anytime in the course of the disease, and could either last considerably long or disappear easily. This study is intended to investigate the occurrence of depression in the course of AD and the risk factors of incidence.