Topological abnormalities of the morphometric similarity network of the cerebral cortex in schizophrenia.

A morphometric similarity (MS) network can be constructed using multiple magnetic resonance imaging parameters of each cortical region. An MS network can be used to assess the similarity between cortical regions. Although MS networks can detect microstructural alterations and capture connections between histologically similar cortical areas, the influence of schizophrenia on the topological characteristics of MS networks remains unclear.

White matter tract alterations in schizophrenia identified by DTI-based probabilistic tractography: a multisite harmonisation study.

Introduction: It has been suggested that schizophrenia involves dysconnectivity between functional brain regions and also the white matter structural disorganisation. Thus, diffusion tensor imaging (DTI) has widely been used for studying schizophrenia. However, most previous studies have used the region of interest (ROI) based approach.

Structural impairment in superficial and deep white matter in schizophrenia.

Objective: Although disconnectivity among brain regions has been one of the main hypotheses for schizophrenia, the superficial white matter (SWM) has received less attention in schizophrenia research than the deep white matter (DWM) owing to the challenge of consistent reconstruction across subjects.

Methods: We obtained the diffusion magnetic resonance imaging (dMRI) data of 223 healthy controls and 143 patients with schizophrenia. After harmonising the raw dMRIs from three different studies, we performed whole-brain two-tensor tractography and fibre clustering on the tractography data.

K-EmoPhone: A Mobile and Wearable Dataset with In-Situ Emotion, Stress, and Attention Labels.

With the popularization of low-cost mobile and wearable sensors, several studies have used them to track and analyze mental well-being, productivity, and behavioral patterns. However, there is still a lack of open datasets collected in real-world contexts with affective and cognitive state labels such as emotion, stress, and attention; the lack of such datasets limits research advances in affective computing and human-computer interaction. This study presents K-EmoPhone, a real-world multimodal dataset collected from 77 students over seven days.

Loss-Framed Adaptive Microcontingency Management for Preventing Prolonged Sedentariness: Development and Feasibility Study.

Background: A growing body of evidence shows that financial incentives can effectively reinforce individuals' positive behavior change and improve compliance with health intervention programs. A critical factor in the design of incentive-based interventions is to set a proper incentive magnitude. However, it is highly challenging to determine such magnitudes as the effects of incentive magnitude depend on personal attitudes and contexts.

Impact of the early phase of the COVID-19 pandemic on the use of mental health services in South Korea: a nationwide, health insurance data-based study.

Purpose: The coronavirus disease 2019 (COVID-19) pandemic has profoundly affected the utilization of mental health services. Existing evidence investigating this issue at the nationwide level is lacking, and it is uncertain whether the effects of the COVID-19 pandemic on the use of psychiatric services differs based on psychiatric diagnosis.

Methods: Data from the claims database between October 2015 and August 2020 was obtained from the Health Insurance Review and Assessment agency in South Korea.

Delay in psychiatric hospitalization from the diagnosis of first-episode schizophrenia and its association with clinical outcomes and direct medical costs: a nationwide, health insurance data-based study.

Background: Early intervention is essential for improving the prognosis in patients with first-episode schizophrenia (FES). The Mental Health Act limits involuntary hospitalization in South Korea to cases where an individual exhibits both a mental disorder and a potential for harming themselves or others, which could result in a delay in the required treatment in FES. We investigated the effect of delay in the first psychiatric hospitalization on clinical outcomes in FES.

One-Year Clinical Outcomes Following Electroconvulsive Therapy for Patients with Schizophrenia: A Nationwide Health Insurance Data-Based Study.

Background: Although the use of electroconvulsive therapy (ECT) in the treatment of schizophrenia has decreased since the advent of antipsychotic drugs, ECT is still implemented in several clinical indications. However, a few population-based studies have examined its real-world effectiveness in schizophrenia.

Methods: We used data from 2010 to 2019 from the Health Insurance Review and Assessment Service database in the Republic of Korea.

A Comparative Study on the Influence of Undersampling and Oversampling Techniques for the Classification of Physical Activities Using an Imbalanced Accelerometer Dataset.

Accelerometer data collected from wearable devices have recently been used to monitor physical activities (PAs) in daily life. While the intensity of PAs can be distinguished with a cut-off approach, it is important to discriminate different behaviors with similar accelerometry patterns to estimate energy expenditure. We aim to overcome the data imbalance problem that negatively affects machine learning-based PA classification by extracting well-defined features and applying undersampling and oversampling methods.

Beyond Pathogen Filtration: Possibility of Smart Masks as Wearable Devices for Personal and Group Health and Safety Management.

Face masks are an important way to combat the COVID-19 pandemic. However, the prolonged pandemic has revealed confounding problems with the current face masks, including not only the spread of the disease but also concurrent psychological, social, and economic complications. As face masks have been worn for a long time, people have been interested in expanding the purpose of masks from protection to comfort and health, leading to the release of various "smart" mask products around the world.

Deep Convolutional Gated Recurrent Unit Combined with Attention Mechanism to Classify Pre-Ictal from Interictal EEG with Minimized Number of Channels.

The early prediction of epileptic seizures is important to provide appropriate treatment because it can notify clinicians in advance. Various EEG-based machine learning techniques have been used for automatic seizure classification based on subject-specific paradigms. However, because subject-specific models tend to perform poorly on new patient data, a generalized model with a cross-patient paradigm is necessary for building a robust seizure diagnosis system.

Comparative effectiveness of antipsychotic monotherapy and polypharmacy in schizophrenia patients with clozapine treatment: A nationwide, health insurance data-based study.

Clozapine is the most effective antipsychotic for treatment-resistant schizophrenia (TRS). However, it remains uncertain whether antipsychotic augmentation to clozapine has the superior effectiveness over clozapine alone and the effect size of clozapine compared to other antipsychotic drugs in TRS. Therefore, we examined the comparative effectiveness of antipsychotic monotherapy and polypharmacy on the risk of psychiatric admission and treatment discontinuation in TRS.

Risk of treatment discontinuation and psychiatric hospitalization associated with early dose reduction of antipsychotic treatment in first-episode schizophrenia: A nationwide, health insurance data-based study.

Aim: We investigated the impact of early dose reduction of antipsychotic treatment on the risk of treatment discontinuation and psychiatric hospitalization in patients with first-episode schizophrenia (FES).

Methods: The Health Insurance Review Agency database in South Korea was used to include 16 153 patients with FES. At 6 months from their diagnosis, the patients were categorized by the magnitude of dose reduction (no reduction, 0%-50%, and >50%).

Diagnostic conversion from unipolar to bipolar affective disorder-A population-based study.

Objectives: It is essential to clinically distinguish bipolar affective disorder from unipolar affective disorders. However, patients previously diagnosed with unipolar affective disorder are sometimes later diagnosed with bipolar affective disorder, known as diagnostic conversion. Here we investigated diagnostic conversion using data from a nationwide population-based register.

Effects of comorbid alcohol use disorder on the clinical outcomes of first-episode schizophrenia: a nationwide population-based study.

Background: Alcohol use disorder (AUD) is a common psychiatric comorbidity in schizophrenia, associated with poor clinical outcomes and medication noncompliance. Most previous studies on the effect of alcohol use in patients with schizophrenia had limitations of small sample size or a cross-sectional design. Therefore, we used a nationwide population database to investigate the impact of AUD on clinical outcomes of schizophrenia.

Hypoparathyroidism, sensorineural deafness, and renal dysgenesis syndrome with a GATA3 mutation.

Hypoparathyroidism, sensorineural deafness, and renal dysgenesis syndrome is an autosomal dominant disease caused by mutations in the GATA3 gene on chromosome 10p15. We identified a patient diagnosed with hypoparathyroidism who also had a family history of hypoparathyroidism and sensorineural deafness, present in the father. The patient was subsequently diagnosed and found to be a heterozygote for an insertion mutation c.