• Journal of Oriental Neuropsychiatry
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• v.34 no.4
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• pp.403-420
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• 2023

Objectives: This study investigated the effectiveness of herbal medicine for generalized anxiety disorder (GAD) based on recent clinical studies. Methods: Studies were searched through four databases. Clinical research studies on herbal medicine treatment for GAD patients were included. The studies were analyzed according to study design, diagnostic criteria, population, and intervention. A risk of bias assessment was performed to assess the quality of the included randomized controlled trials (RCT). If the intervention applied to the treatment and control groups was the same and two or more studies were reporting the same items as outcome indicators, a meta-analysis was performed. Results: A total of 19 studies, including 12 RCTs were selected. The most common pattern identification was 'Phlegm fire disturbing upward' (痰熱上擾), and the most used herb for therapeutic purposes was 'Rhizome of Poria cocos' (茯苓). Meta-analysis results of three studies showed that there were no significant differences in effectiveness between the herbal medicine intervention and the Western medicine intervention. Meta-analysis results of five studies showed that the Hamilton Anxiety Rating Scale was significantly reduced in the case of herbal medicine intervention compared to Western medicine intervention. Conclusions: The results of our study demonstrated that herbal medicine treatment for GAD is effective in alleviating anxiety symptoms and chief symptoms of GAD. However, this study has several limitations; there was a lack of placebo-controlled RCT and an absence of objective diagnostic criteria in case reports. Therefore, further well-designed clinical studies, conducted based on the results of this study, are recommended.

• Journal of Oriental Neuropsychiatry
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• v.34 no.4
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• pp.369-384
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• 2023

Objectives: The purpose of this study was to review the recent clinical studies on Korean medicine for treatment of eating disorders. Methods: We searched clinical studies that verified the effectiveness of Korean medicine for the treatment of eating disorders. The search was done in 9 databases (Korean, Chinese, and English databases) from January 2016 to August 2023. Results: A total of 10 articles were retrieved. The articles were classified based on the type of study design: 1 database study, 2 case series, and 7 case reports. Among the articles, in 4 articles, acupuncture was used as a treatment intervention for bulimia nervosa, and in 6 articles herbal medicine was used as a treatment intervention for anorexia nervosa. The most frequent pattern identification was 'Liver qi depression', the most composed herb was 'Root of Glycyrrhiza uralensis (甘草)', and the most used acupoints were CV12 and SP6. All the studies showed positive results. Conclusions: Korean medicine for eating disorders treatments might be effective. However, the quality of evidence in the selected studies was low, and there was no comparison of the treatment effects using objective diagnostic tools. For more accurate results, systematically designed clinical studies using objective diagnostic tools should be conducted.

• Information Systems Review
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• v.25 no.3
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• pp.27-41
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• 2023

Unlike the previous works focusing on the state-of-the-art methodologies to improve the performance of machine learning models, this study improves the 'quality' of training data used in machine learning. We propose a method to enhance the quality of training data through the processing of 'local grammar,' frequently used in corpus analysis. We collected a vast amount of unstructured corporate review text data posted by employees working in the top 100 companies in Korea. After improving the data quality using the local grammar process, we confirmed that the classification model with local grammar outperformed the model without it in terms of classification performance. We defined five factors of work engagement as classification categories, and analyzed how the pattern of reviews changed before and after the COVID-19 pandemic. Through this study, we provide evidence that shows the value of the local grammar-based automatic identification and classification of employee experiences, and offer some clues for significant organizational cultural phenomena.

• Journal of the Korean Society of Radiology
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• v.83 no.6
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• pp.1240-1258
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• 2022

The lymphatic system provides a route for the spread of inflammation and malignancies. The identification of nodal stations and lymphatic pathways of tumor spread is important for tumor staging, choice of therapy, and the prediction of the prognosis of patients with malignant diseases. Because lymph node metastasis is common in primary intra-abdominal malignant tumors, its detection is essential for radiologists to understand the pattern of disease spread. Using schematic pictures and color-coded CT images, this pictorial essay describes the locations and nomenclature of the abdominal lymph nodes. Furthermore, the lymphatic drainage pathways of the upper and lower gastrointestinal tracts, liver, gallbladder, bile duct, and pancreas have been highlighted. In addition, lymph nodes belonging to the regional lymph nodes in malignant tumors arising from each organ are described, and certain cases are presented with images from patients.

• Journal of the Korean Society of Radiology
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• v.82 no.4
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• pp.770-790
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• 2021

Idiopathic pulmonary fibrosis (IPF), based on the 2018 international clinical practice guidelines, can be diagnosed with a usual interstitial pneumonia (UIP) pattern on high-resolution computed tomography (HRCT) and compatible clinical findings. Given that imaging is pivotal for IPF evaluation and diagnosis, more emphasis should be placed on the integration of clinical, radiological, and pathologic findings for multidisciplinary diagnosis. Interstitial lung abnormality (ILA), on the other hand, has a purely radiological definition based on the incidental identification of CT abnormalities. Taken together, differentiation between ILA and clinically significant interstitial lung disease (ILD) must be based on proper clinical evaluation. With this review, the recent updates in IPF diagnosis and the radiologic considerations for ILA can be well understood, which can be helpful for the proper diagnosis and management of patients with diffuse interstitial pulmonary fibrosis.

• Analytical Science and Technology
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• v.37 no.1
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• pp.25-38
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• 2024

The study aimed to investigate a novel approach by utilizing liquid chromatography (LC) and liquid chromatography-mass spectrometry (LC-MS) to separate, identify and characterize very nominal quantities of degradation products (DPs) of balsalazide along with its process related impurities without isolation from their reaction mixtures. The impurities along with balsalazide were resolved on spherisorb ODS2 (250×4.6 mm, 5.0 ㎛) column at room temperature using 0.2 M sodium acetate solution at pH 4.5 and methanol in the ratio of 55:45 (v/v) as mobile phase pumped isocratically at 1.0 mL/min as mobile phase and UV detection at 255 nm. The method shows sensitive detection limit of 0.003 ㎍/mL, 0.015 ㎍/mL and 0.009 ㎍/mL respectively for impurity 1, 2 and 3 with calibration curve liner in the range of 50-300 ㎍/mL for balsalazide and 0.05-0.30 for its impurities. The balsalazide pure compound was subjected to stress studies and a total of four degradation products (DPs) were formed during the stress study and all the DPs were characterized with the help of their fragmentation pattern and the masses obtained upon LC-MS/MS. The DPs were identified as 3-({4-[(E)-(4-hydroxyphenyl) diazenyl]benzoyl}amino)propanoic acid (DP 1), 4-[(E)-(4-hydroxyphenyl)diazenyl] benzamide (DP 2), 5-[(E)-(4-carbamoylphenyl)diazenyl]-2-hydroxybenzoic acid (DP 3) and 3-({4-[(E)-phenyldiazenyl]benzoyl}amino)propanoic acid (DP 4). Based on findings, it was concluded that, the proposed method was successfully applicable for routine analysis of balsalazide and its process related impurities in pure drug and formulations and also applicable for identification of known and unknown impurities of balsalazide.

• The Transactions of the Korea Information Processing Society
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• v.13 no.3
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• pp.130-139
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• 2024

Artificial intelligence models are being used to detect facility anomalies using physics data such as vibration, current, and temperature for predictive maintenance in the manufacturing industry. Since the types of facility anomalies, such as facility defects and failures, anomaly detection methods using autoencoder-based unsupervised learning models have been mainly applied. Normal or abnormal facility conditions can be effectively classified using the reconstruction error of the autoencoder, but there is a limit to identifying facility anomalies specifically. When facility anomalies such as unbalance, misalignment, and looseness occur, the facility vibration frequency shows a pattern different from the normal state in a specific frequency range. This paper presents an N-segmentation anomaly detection method that performs anomaly detection by dividing the entire vibration frequency range into N regions. Experiments on nine kinds of anomaly data with different frequencies and amplitudes using vibration data from a compressor showed better performance when N-segmentation was applied. The proposed method helps materialize them after detecting facility anomalies.

• Smart Structures and Systems
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• v.33 no.2
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• pp.93-103
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• 2024

Despite the rapid development of sensors, structural health monitoring (SHM) still faces challenges in monitoring due to the degradation of devices and harsh environmental loads. These challenges can lead to measurement errors, missing data, or outliers, which can affect the accuracy and reliability of SHM systems. To address this problem, this study proposes a classification method that detects anomaly patterns in sensor data. The proposed classification method involves several steps. First, data scaling is conducted to adjust the scale of the raw data, which may have different magnitudes and ranges. This step ensures that the data is on the same scale, facilitating the comparison of data across different sensors. Next, informative features in the time and frequency domains are extracted and used as input for a deep neural network model. The model can effectively detect the most probable anomaly pattern, allowing for the timely identification of potential issues. To demonstrate the effectiveness of the proposed method, it was applied to actual data obtained from a long-span cable-stayed bridge in China. The results of the study have successfully verified the proposed method's applicability to practical SHM systems for civil infrastructures. The method has the potential to significantly enhance the safety and reliability of civil infrastructures by detecting potential issues and anomalies at an early stage.

• Journal of Preventive Medicine and Public Health
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• v.11 no.1
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• pp.123-127
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• 1978

The major objective of this research is to identify those hospital characteristics that best explain cost variation among hospitals and to formulate linear models that can predict hospital costs. Specific emphasis is placed on hospital output, that is, the identification of diagnosis related patient groups (DRGs) which are medically meaningful and demonstrate similar patterns of hospital resource consumption. A casemix index is developed based on the DRGs identified. Considering the common problems encountered in previous hospital cost research, the following study requirements are estab-lished for fulfilling the objectives of this research: 1. Selection of hospitals that exercise similar medical and fiscal practices. 2. Identification of an appropriate data collection mechanism in which demographic and medical characteristics of individual patients as well as accurate and comparable cost information can be derived. 3. Development of a patient classification system in which all the patients treated in hospitals are able to be split into mutually exclusive categories with consistent and stable patterns of resource consumption. 4. Development of a cost finding mechanism through which patient groups' costs can be made comparable across hospitals. A data set of Medicare patients prepared by the Social Security Administration was selected for the study analysis. The data set contained 27,229 record abstracts of Medicare patients discharged from all but one short-term general hospital in Connecticut during the period from January 1, 1971, to December 31, 1972. Each record abstract contained demographic and diagnostic information, as well as charges for specific medical services received. The 'AUT-OGRP System' was used to generate 198 DRGs in which the entire range of Medicare patients were split into mutually exclusive categories, each of which shows a consistent and stable pattern of resource consumption. The 'Departmental Method' was used to generate cost information for the groups of Medicare patients that would be comparable across hospitals. To fulfill the study objectives, an extensive analysis was conducted in the following areas: 1. Analysis of DRGs: in which the level of resource use of each DRG was determined, the length of stay or death rate of each DRG in relation to resource use was characterized, and underlying patterns of the relationships among DRG costs were explained. 2. Exploration of resource use profiles of hospitals; in which the magnitude of differences in the resource uses or death rates incurred in the treatment of Medicare patients among the study hospitals was explored. 3. Casemix analysis; in which four types of casemix-related indices were generated, and the significance of these indices in the explanation of hospital costs was examined. 4. Formulation of linear models to predict hospital costs of Medicare patients; in which nine independent variables (i. e., casemix index, hospital size, complexity of service, teaching activity, location, casemix-adjusted death. rate index, occupancy rate, and casemix-adjusted length of stay index) were used for determining factors in hospital costs. Results from the study analysis indicated that: 1. The system of 198 DRGs for Medicare patient classification was demonstrated not only as a strong tool for determining the pattern of hospital resource utilization of Medicare patients, but also for categorizing patients by their severity of illness. 2. The wei틴fed mean total case cost (TOTC) of the study hospitals for Medicare patients during the study years was $11,27.02 with a standard deviation of $117.20. The hospital with the highest average TOTC ($1538.15) was 2.08 times more expensive than the hospital with the lowest average TOTC ($743.45). The weighted mean per diem total cost (DTOC) of the study hospitals for Medicare patients during the sutdy years was $107.98 with a standard deviation of $15.18. The hospital with the highest average DTOC ($147.23) was 1.87 times more expensive than the hospital with the lowest average DTOC ($78.49). 3. The linear models for each of the six types of hospital costs were formulated using the casemix index and the eight other hospital variables as the determinants. These models explained variance to the extent of 68.7 percent of total case cost (TOTC), 63.5 percent of room and board cost (RMC), 66.2 percent of total ancillary service cost (TANC), 66.3 percent of per diem total cost (DTOC), 56.9 percent of per diem room and board cost (DRMC), and 65.5 percent of per diem ancillary service cost (DTANC). The casemix index alone explained approximately one half of interhospital cost variation: 59.1 percent for TOTC and 44.3 percent for DTOC. Thsee results demonstrate that the casemix index is the most importand determinant of interhospital cost variation Future research and policy implications in regard to the results of this study is envisioned in the following three areas: 1. Utilization of casemix related indices in the Medicare data systems. 2. Refinement of data for hospital cost evaluation. 3. Development of a system for reimbursement and cost control in hospitals.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.4
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• pp.1690-1698
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• 2012

As alcohol use is one of the most important risk factors for injuries, this study was intended to clarify and evaluate any relationship between drinking patterns and the incidence rates/specific characteristics of injuries in adult populations, using a widely accepted tool, the Alcohol Use Disorders Identification Test (chronic alcohol drinking behaviors measurement, hereinafter the AUDIT) developed by the World Health Organization to help to assess the behaviors in a more accurate and reliable manner. This study used the data collected from the 2009 Korea National Health and Nutrition Examination Survey (KNHANES), in which 7,511 of 7,893 adult participants aged ${\geq}19$ years answered the questions about injuries, and excluding 104 non-respondents, 6,258 of participants in the questionnaire survey of drinking patterns were finally analyzed. The incidence rates and specific characteristics of injuries as classified by the AUDIT categories (i.e., body regions, types and mechanisms) were assessed and estimated in terms of their relative risk using t-test, ANOVA, and logistic regression. SPSS 19.0 statistical package software was employed for statistical analyses. These analyses indicate that the incidence rates of overall injuries were significantly higher in male respondents than in female respondents. The risks of alcohol use related injuries were 8.3 times higher in male respondents than in female ones. Regarding educational background, high school graduates showed the highest rates in the AUDIT with significant difference from the other groups. The married group and the group of respondents having monthly income estimated at KRW 2.01 to 3 million also showed the highest rates in the AUDIT compared to the other groups, indicating statistically significant difference. Significantly increased in problematic drinkers and those with alcohol dependence, the incidence rate of injuries body regions was 0.0371 in the head/neck, and with respect to the AUDIT and the mechanisms of external causes of injuries, transport accidents ranked first, followed by slippage, others, crash and fall. In regard to the classified types of injuries, it was statistically significant in others (e.g., laceration, contusion, addiction, or penetrating wound). In conclusion, the mechanisms of external causes of injuries as well as injuries attributed to alcohol use are very important, and a strategy is required to reduce such the injuries in the manner of decreasing the frequency of drinking after motivation by professional counsellors.