• Journal of the Korean Child Neurology Society
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• v.25 no.3
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• pp.204-207
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• 2017

Hyperornithinemia-hyperammonemia-homocitrullinuria syndrome (HHH syndrome) is a neurometabolic disorder with highly variable clinical severity ranging from mild learning disability to severe encephalopathy. Diagnosis of HHH syndrome can easily be delayed or misdiagnosed due to insidious symptoms and incomplete biochemical findings, in that case, genetic testing should be considered to confirm the diagnosis. HHH syndrome is caused by biallelic mutations of SLC25A15, which is involved in the urea cycle and the ornithine transport into mitochondria. Here we report a boy with spastic paraplegia and asymptomatic younger sister who have compound heterozygous mutations of c.535C>T (p.R179^*) and c.116C>A (p.T39K) in the SLC25A15 gene. We identified that p.T39K mutation is a novel pathogenic mutation causing HHH syndrome and that p.R179^*, which is prevalent in Japanese and Middle Eastern heritage, is also found in the Korean population.

• Korean Journal of Schizophrenia Research
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• v.20 no.1
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• pp.15-22
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• 2017

Objectives : It has been shown that early intervention is crucial for favorable outcome in patients with schizophrenia. However, development of biomarkers for predicting prognosis of psychotic disorder still requires more research. In this study, we aimed to investigate whether baseline mismatch negativity (MMN) predict prognosis in patients with first episode psychosis (FEP). Methods : Twenty-four patients with FEP and matched healthy controls (HCs) were examined with MMN at baseline, and their clinical status were re-assessed after 1 year. Repeated-measures analysis of variance was performed to compare baseline MMN between the two groups. Multiple regression analysis was used to identify factors predicting prognosis in FEP patients during the follow-up period. Results : MMN amplitudes at baseline were significantly reduced in patients with FEP compared to healthy controls. In the multiple regression analysis, baseline MMN amplitude significantly predicted later improvement of performances on digit span and delayed recall of California Verbal Learning Test. However, baseline MMN did not predicted improvement of clinical symptoms. Conclusion : These results indicate that MMN may be a possible predictor of improvement in cognitive functioning in patients with FEP. Future study with larger sample and longer follow-up period would be needed to confirm the findings of the current study.

• The korean journal of orthodontics
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• v.54 no.4
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• pp.229-238
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• 2024

Objective: The study aimed to assess the prevalence of dental malocclusion, orthodontic parameters, and parafunctional habits in children with developmental dyslexia (DD). Methods: Forty pediatric patients (67.5% boys and 32.5% girls, mean age: 11.02 ± 2.53 years, range: 6-15 years) with DD were compared with 40 age- and sex-matched healthy participants for prevalence of dental malocclusion, orthodontic parameters, and parafunctional habits. Dental examinations were performed by an orthodontist. Results: Pediatric patients with DD exhibited a significantly higher prevalence of Angle Class III malocclusion (22.5% vs. 5.0%, P = 0.024), deep bite (27.5% vs. 7.5%, P = 0.019), midline deviation (55.0% vs. 7.5%, P < 0.0001), midline diastemas (32.5% vs. 7.5%, P = 0.010), wear facets (92.5% vs. 15.0%, P < 0.0001), self-reported nocturnal teeth grinding (82.5% vs. 7.5%, P < 0.0001), nail biting (35.0% vs. 0.0%, P < 0.0001), and atypical swallowing (85.0% vs. 17.5%, P < 0.0001) compared to that in healthy controls. Conclusions: Pediatric patients with DD showed a higher prevalence of Class III malocclusion, greater orthodontic vertical and transverse discrepancies, and incidence of parafunctional activities. Clinicians and dentists should be aware of the vulnerability of children with dyslexia for exhibiting malocclusion and encourage early assessment and multidisciplinary intervention.

• The Journal of the Korea Contents Association
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• v.22 no.3
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• pp.354-360
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• 2022

Metabolic disease is a disease with a prevalence of 26% in Korean, and has three of the five states of abdominal obesity, hypertension, hunger glycemic disorder, high neutral fat, and low HDL cholesterol at the same time. This paper links the consumer panel data of the Rural Development Agency(RDA) and the medical care data of the National Health Insurance Service(NHIS) to generate a classification model that can be divided into a metabolic disease group and a control group through food consumption characteristics, and attempts to compare the differences. Many existing domestic and foreign studies related to metabolic diseases and food consumption characteristics are disease correlation studies of specific food groups and specific ingredients, and this paper is logistic considering all food groups included in the general diet. We created a classification model using regression, a decision tree-based classification model, and a classification model using XGBoost. Of the three models, the high-precision model is the XGBoost classification model, but the accuracy was not high at less than 0.7. As a future study, it is necessary to extend the observation period for food consumption in the patient group to more than 5 years and to study the metabolic disease classification model after converting the food consumed into nutritional characteristics.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.8
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• pp.371-380
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• 2023

Relation extraction is to extract relationships between named entities from text. Traditionally, relation extraction methods only extract relations between predetermined subject and object entities. However, in end-to-end relation extraction, all possible relations must be extracted by considering the positions of the subject and object for each pair of entities, and so this method uses time and resources inefficiently. To alleviate this problem, this paper proposes a method that sets directions based on the positions of the subject and object, and extracts relations according to the directions. The proposed method utilizes existing relation extraction data to generate direction labels indicating the direction in which the subject points to the object in the sentence, adds entity position tokens and entity type to sentences to predict the directions using a pre-trained language model (KLUE-RoBERTa-base, RoBERTa-base), and generates representations of subject and object entities through probabilistic crossover operation. Then, we make use of these representations to extract relations. Experimental results show that the proposed model performs about 3 ~ 4%p better than a method for predicting integrated labels. In addition, when learning Korean and English data using the proposed model, the performance was 1.7%p higher in English than in Korean due to the number of data and language disorder and the values of the parameters that produce the best performance were different. By excluding the number of directional cases, the proposed model can reduce the waste of resources in end-to-end relation extraction.

• Journal of Korean Ophthalmic Optics Society
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• v.18 no.2
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• pp.125-136
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• 2013

Purpose: The aim of this study was to investigate the effect of improving read speed with color filter or without color filter to improve reading disorder of teenager who were diagnosed as Meares-Irlen syndrome through survey inspection with Meares-Irlen syndrome visual stress (MISViS) score. Methods: MISViS subjects were selected from screening survey MISViS results given above 2.13 in the clinical criteria scores (MISViS score). Reading speed were measured quickly and efficiently the rate of reading via test in which randomly ordered common words are read aloud during a minute. Each of the subjects were worn a filter of the lowest concentration in each color filter group composed of 15 groups. Results: MISViS score of MISViS group and control group were 2.57 and 0.66, respectively. Results of reading speed with filter and without filter in MISViS group were $102.27{\pm}27.86$ wpm and $118.87{\pm}26.99$ wpm (p=0.001), respectively, as well as were $132.93{\pm}6.88$ wpm and $133.43{\pm}6.64$ wpm (p=0.131) in the normal group. Associated with error changes with filter and without filter between two groups, skipping in MISViS Group were from $0.25{\pm}0.62$ times to 0 times (p=0.191), Errors were from $1.83{\pm}1.69$ times to $0.17{\pm}0.38$ times (p = 0.004) and, repetitions were 0. skipping in control group were 0 times, errors were from $0.21{\pm}0.43$ times to $0.07{\pm}0.27$ times (p=0.336) and, repetitions were from $0.14{\pm}0.36$ times to 0 (p=0.165). The filter of blue series chosen in MISViS group had higher percentage (40%), whereas, subjects in normal group were more likely to prefer the filter of gray color (29%). Conclusions: This study showed that MISViS score have been used as a significant diagnosis for Irlen syndrome screening. This study found that wearing suitable color filter for MISViS patients were useful to improve learning with regard to reading. Unique color filter selection for MISViS subjects must be carefully considered since fit color filter are different personally.

• Journal of the Korean Society of Radiology
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• v.17 no.5
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• pp.767-773
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• 2023

To In this study, we sought to evaluate related factors affecting lung volume and their significance in pulmonary function and ventilation disorders. As experimental subjects, 206 normal adult men and women who underwent a low-dose chest CT scan and a spirometry test were selected at the same time. The experimental method was to measure lung volume using lung CT images obtained through a low-dose chest CT scan using deep learning-based AVIEW. Measurements were made using the LCS automatic diagnosis program. In addition, the results of measuring lung function were obtained using a spirometer, and gender and BMI were selected as related factors that affect lung volume, and significance was evaluated through an independent sample T-test with lung volume. As a result of the experiment, it was confirmed that in evaluating lung volume according to gender, all lung volumes of men were larger than all lung volumes of women. he result of an independent samples T-test using the respective average values for gender and lung volume showed that all lung volumes were larger in men than in women, which was significant (p<0.001). And in the evaluation of lung volume according to BMI index, it was confirmed that all lung volumes of adults with a BMI index of 24 or higher were larger than all lung volumes of adults with a BMI index of less than 24. However, the independent samples T-test using the respective average values for BMI index and lung volume did not show a significant result that all lung volumes were larger in BMI index 24 or higher than in BMI index less than 24 (p<0.055). In the evaluation of lung volume according to the presence or absence of pulmonary ventilation impairment, it was confirmed that all lung volumes of adults with normal pulmonary function ventilation were larger than all lung volumes of adults with pulmonary ventilation impairment. And as a result of the independent sample T-test using the respective average values for the presence or absence of pulmonary ventilation disorder and lung volume, the result was significant that all lung volumes were larger in adults with normal pulmonary function ventilation than in adults with pulmonary function ventilation disorder (p <0.001). Lung volume and spirometry test results are the most important indicators in evaluating lung health, and using these two indicators together to evaluate lung function is the most accurate evaluation method. Therefore, it is expected that this study will be used as basic data by presenting the average lung volume for adults with normal ventilation and adults with impaired lung function and ventilation in similar future studies on lung volume and vital capacity testing.

• The Journal of Korean Academy of Sensory Integration
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• v.16 no.1
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• pp.45-55
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• 2018

Objective : The purpose of this systematic review was to inform intervention of sensory integration in adult patients and to provide evidence regarding occupational therapy. Methods : Studies for this review were collected by searching the Pubmed, Scopus, SAGE Journal, Medline, RISS database for articles from 1980 to 2017, using the following keywords: "(sensory integration OR sensory processing OR sensory integrative OR sensory based OR sensory defensiveness) AND adult" A total of 8 studies were included in the analysis. The selected papers were analyzed by using PICO (Patient, Intervention, Comparison, Outcome) framework. Results : The participants' diagnoses were learning disabilities, intellectual disability, dementia and sensory processing disorder. Assessment tools and intervention methods varied according to the researcher's intent. In most studies, sensory integration intervention was shown to be effective. Conclusion : This study was able to confirm that sensory integration intervention was available and effective for adult patients. This was intended to provide clinical evidence for occupational therapists, and further studies should be conducted to establish the application of sensory integration interventions to adults based on this study.

• Journal of Korea Game Society
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• v.10 no.6
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• pp.115-124
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• 2010

In the beginning brain waves were used for monkeys to control robot arm with neural activity. In recent years there are research that measured brain waves are used for the control of programs which monitor the progression of dementia or enhance of attention in children diagnosed with Attention Deficit Hyperactivity Disorder (ADHD). Moreover, low-price devices that can be used as a game control interface have become available. One of the problems associated with control using brain waves is that the mean amplitude, mean wavelength, and mean vibrational frequency of the brain waves differ from individual to individual. This paper attempts to propose a method to normalize measured brain waves using normal distribution and calculate the waveforms that can be used in controlling games. For this, a framework in which brain waves are converted in seven stages has been suggested. In addition, the estimation process in each stage has been described. In an experiment the waveforms of two subjects have been compared using the proposed method in the BCI English word learning program. The level of similarity between two subjects' waveforms has been compared with correlation coefficient. When the proposed method was applied, both meditation and concentration increased by 13% and 8%, respectively. Because the proposed regularization method is converted into a waveform fit for control functions by reducing personal characteristics reflected in the brain waves, it is fitting for application programs such as games.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.42 no.3 s.303
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• pp.47-52
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• 2005

Obstructive Sleep Apnea (OSA) is a representative symptom of sleep disorder caused by the obstruction of upper airway. Because OSA causes not only excessive daytime sleepiness and fatigue, hypertension and arrhythmia but also cardiac arrest and sudden death during sleep in the severe case, it is very important to detect the occurrence and the frequency of OSA. OSA is usually diagnosed through the laboratory-based Polysomnography (PSG) which is uncomfortable and expensive. Therefore researches to improve the disadvantages of PSG are needed and studies for the detection of OSA using only one or two parameters are being made as alternatives to PSG. In this paper, we developed an algorithm for the detection of OSA based on Heart Rate Variability (HRV). The proposed method is applied to the ECG data sets provided from PhysioNet which consist of learning set and training set. We extracted features for the detection of OSA such as average and standard deviation of 1 minute R-R interval, power spectrum of R-R interval and S-peak amplitude from data sets. These features are applied to the input of neural network. As a result, we obtained sensitivity of $89.66\%$ and specificity of $95.25\%$. It shows that the features suggested in this study are useful to detect OSA.