• PNF and Movement
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• v.22 no.1
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• pp.101-111
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• 2024

Purpose: The purpose of this study was to investigate physical activity as a risk factor for neck pain recurrence using the National Health Insurance Data Sharing Service that utilizes a nationwide cohort in South Korea. Methods: Medical records spanning a two-year period were extracted from the National Health Insurance database for 541,937 patients who sought healthcare services for neck pain (ICD 10 codes: M54.2) in 2020 and completed the national health examination survey. Selected variables for analysis included age, gender, health insurance premium decile, regional health vulnerability index, body mass index (BMI), acuity, blood pressure, and types of physical activity. A mixed-effect multivariate logistic regression analysis was conducted to examine the recurrence rate of neck pain and identify risk factors for neck pain recurrence. Results: Among the participants, 124,433 patients (23.0%) experienced a recurrence of neck pain within two years, with higher recurrence rates observed among older individuals and females. Regression analysis revealed that the risk of neck pain recurrence increased with age (OR=1.51), being female (OR= 1.10), being a medical aid recipient (OR=1.51), and having anaerobic (OR=1.04) or vigorous physical activities (OR=1.06). By contrast, an increased health insurance premium decile (OR=0.96) and having moderate physical activity (OR=0.97) were associated with a decreased risk of neck pain recurrence. Conclusion: This study highlights the importance of moderate physical activity as an effective strategy for reducing the recurrence of nonspecific neck pain, underscoring the necessity for personalized physical activity programs for patients.

• Journal of dental hygiene science
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• v.24 no.1
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• pp.9-21
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• 2024

Background: The purpose of this study was to utilize text network analysis and topic modeling to identify interconnected relationships among keywords present in patent information related to oral health, and subsequently extract latent topics and visualize them. By examining key keywords and specific subjects, this study sought to comprehend the technological trends in oral health-related innovations. Furthermore, it aims to serve as foundational material, suggesting directions for technological advancement in dentistry and dental hygiene. Methods: The data utilized in this study consisted of information registered over a 20-year period until July 31st, 2023, obtained from the patent information retrieval service, KIPRIS. A total of 6,865 patent titles related to keywords, such as "dentistry," "teeth," and "oral health," were collected through the searches. The research tools included a custom-designed program coded specifically for the research objectives based on Python 3.10. This program was used for keyword frequency analysis, semantic network analysis, and implementation of Latent Dirichlet Allocation for topic modeling. Results: Upon analyzing the centrality of connections among the top 50 frequently occurring words, "method," "tooth," and "manufacturing" displayed the highest centrality, while "active ingredient" had the lowest. Regarding topic modeling outcomes, the "implant" topic constituted the largest share at 22.0%, while topics concerning "devices and materials for oral health" and "toothbrushes and oral care" exhibited the lowest proportions at 5.5% each. Conclusion: Technologies concerning methods and implants are continually being researched in patents related to oral health, while there is comparatively less technological development in devices and materials for oral health. This study is expected to be a valuable resource for uncovering potential themes from a large volume of patent titles and suggesting research directions.

• Journal of the Health Care and Life Science
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• v.10 no.2
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• pp.265-274
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• 2022

In this paper, the 2018 elderly patient data sets among the patient sample data of the Health Insurance Review & Assessment Service and the 260,425 statements of patients admitted to the long-term care hospitals were together used. Accordingly, the characteristics of each hospital type were analyzed by classifying the addition type of long-term care hospitals according to whether or not to secure the required manpower and whether or no to secure more than two-thirds of required nurses. However, in evaluating whether or not to secure more than 2/3 of necessary nurses and whether or not to secure the necessary manpower, the relative value points were not considered, and the same amounts of value has been maintained for 13 years, so the relevant value needs to be revised.

• Journal of Preventive Medicine and Public Health
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• v.49 no.4
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• pp.230-239
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• 2016

Objectives: We aimed to evaluate the effect of geographic units of analysis on measuring geographic variation in medical services utilization. For this purpose, we compared geographic variations in the rates of eight major procedures in administrative units (districts) and new areal units organized based on the actual health care use of the population in Korea. Methods: To compare geographic variation in geographic units of analysis, we calculated the age-sex standardized rates of eight major procedures (coronary artery bypass graft surgery, percutaneous transluminal coronary angioplasty, surgery after hip fracture, knee-replacement surgery, caesarean section, hysterectomy, computed tomography scan, and magnetic resonance imaging scan) from the National Health Insurance database in Korea for the 2013 period. Using the coefficient of variation, the extremal quotient, and the systematic component of variation, we measured geographic variation for these eight procedures in districts and new areal units. Results: Compared with districts, new areal units showed a reduction in geographic variation. Extremal quotients and inter-decile ratios for the eight procedures were lower in new areal units. While the coefficient of variation was lower for most procedures in new areal units, the pattern of change of the systematic component of variation between districts and new areal units differed among procedures. Conclusions: Geographic variation in medical service utilization could vary according to the geographic unit of analysis. To determine how geographic characteristics such as population size and number of geographic units affect geographic variation, further studies are needed.

• Laboraroty Animal Research
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• v.34 no.4
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• pp.311-316
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• 2018

Laboratory inbred mice are used widely and commonly in biomedical research, but inbred mice do not have a big enough gene pool for the research. In this study, genetic and morphometric analyses were performed to obtain data on the characteristics of a newly developing inbred strain (KWM/Hym) captured from Chuncheon, Korea. All of five Korean wild male mice have the zinc-finger Y (ZfY) gene. Also, all of 19 Korean wild mice used in this analysis have the AKV-type murine leukemia virus gene, indicating that Korean wild mice might be Mus musculus musculus. To identify the genetic polymorphism in KWM/Hym, SNP analysis was performed. In a comparison with 28 SNP markers, there was a considerable difference between KWM/Hym and several inbred strains. The homogeneity between KWM/Hym and the inbred strains was as follows: C57BL/6J (39.3%), BALB/c AJic (42.9%), and DBA/2J (50%). KWM/Hym is most similar to the PWK/PhJ inbred strain (96.4%) derived from wild mice (Czech Republic). To identify the morphometric characteristics of KWM/Hym, the external morphology was measured. The tail ratio of male and female was $79.60{\pm}3.09$ and $73.55{\pm}6.14%$, respectively. KWM/Hym has short and agouticolored hairs and its belly is white with golden hair. Taking these results together, KWM/Hym, a newly developing inbred mouse originated from wild mouse, might be use as new genetic resources to overcome the limitations of the current laboratory mice.

• Korean Journal of Legislative Studies
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• v.26 no.3
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• pp.125-159
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• 2020

Amid global pandemic of covid-19, Korean government's response has drawn wide attention among social scientists as well as medical studies. The role of Korean state and civil society has attracted particular attention among others. Yet, this paper criticizes extant studies on Korean case which focus on the extensive intervention of the strong state and subjective attitude of Korean citizens in coping with covid-19. The concept of the strong state lacks social scientific specification and subjective citizens do not match with Korean realities. This article argues that Korean state's capacity in collecting and mobilizing digital data may offer better understanding for the successful responses to the pandemic. First, Korean state is the ultimate coordinator in collecting, analyzing and applying big data about the expansion of covid-19 with its huge network of dataveillance. Also, such role has been largely based upon relevant legal framework and well prepared manuals and cooperation with civic actors and companies. In other words, Korean digital dataveillance had demonstrated its transparency and cooperative governance. Second, such dataveillance capacity has deep roots in the long-term development of Korean state's big data management. Korean state has evolved about thirty years while enhancing digital data network within governments, companies and private sectors. Third, the relationship between Korean state's dataveillance and civil society can be characterized as a state centered push model. This model demonstrates highly effective governmental responses to covid-19 crisis but fall short of building social consensus in balancing individual freedom, human rights and effective containment policies. It means communitarian solidarity among citizens has not been a major factor in Korea's successful response yet.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.4
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• pp.2060-2077
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• 2019

Recently, mobile healthcare services have attracted significant attention because of the emerging development and supply of diverse wearable devices. Smartwatches and health bands are the most common type of mobile-based wearable devices and their market size is increasing considerably. However, simple value comparisons based on accumulated data have revealed certain problems, such as the standardized nature of health management and the lack of personalized health management service models. The convergence of information technology (IT) and biotechnology (BT) has shifted the medical paradigm from continuous health management and disease prevention to the development of a system that can be used to provide ground-based medical services regardless of the user's location. Moreover, the IT-BT convergence has necessitated the development of lifestyle improvement models and services that utilize big data analysis and machine learning to provide mobile healthcare-based personal health management and disease prevention information. Users' health data, which are specific as they change over time, are collected by different means according to the users' lifestyle and surrounding circumstances. In this paper, we propose a prediction model of user physical activity that uses data characteristics-based long short-term memory (DC-LSTM) recurrent neural networks (RNNs). To provide personalized services, the characteristics and surrounding circumstances of data collectable from mobile host devices were considered in the selection of variables for the model. The data characteristics considered were ease of collection, which represents whether or not variables are collectable, and frequency of occurrence, which represents whether or not changes made to input values constitute significant variables in terms of activity. The variables selected for providing personalized services were activity, weather, temperature, mean daily temperature, humidity, UV, fine dust, asthma and lung disease probability index, skin disease probability index, cadence, travel distance, mean heart rate, and sleep hours. The selected variables were classified according to the data characteristics. To predict activity, an LSTM RNN was built that uses the classified variables as input data and learns the dynamic characteristics of time series data. LSTM RNNs resolve the vanishing gradient problem that occurs in existing RNNs. They are classified into three different types according to data characteristics and constructed through connections among the LSTMs. The constructed neural network learns training data and predicts user activity. To evaluate the proposed model, the root mean square error (RMSE) was used in the performance evaluation of the user physical activity prediction method for which an autoregressive integrated moving average (ARIMA) model, a convolutional neural network (CNN), and an RNN were used. The results show that the proposed DC-LSTM RNN method yields an excellent mean RMSE value of 0.616. The proposed method is used for predicting significant activity considering the surrounding circumstances and user status utilizing the existing standardized activity prediction services. It can also be used to predict user physical activity and provide personalized healthcare based on the data collectable from mobile host devices.

• Journal of Biomedical Engineering Research
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• v.33 no.1
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• pp.32-38
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• 2012

Recently, several ultrasound imaging techniques for tissue characterization have been developed. Among them, ultrasound elastography is regarded as the most promising modality and has been rapidly developed. One of ultrasound elastography techniques is shear modulus imaging. Normal and cancerous tissues show big difference of shear moduli and they have good image contrast. However shear wave elastography requires more complicated hardware and more computations for image reconstruction algorithm. Therefore new efficient techniques are being developed. In this paper, we have developed a very flexible ultrasound system for elastography experiments. The developed system has capabilities to acquire ultrasound RF data of all channels and generate arbitrary ultrasound pulse sequences. It has a huge amount of memories for RF data acquisition and a simple and flexible pulse generator. We have verified the performance of the system showing conventional B-mode images and preliminary results of elastography. The developed system will be used to verify our own reconstruction algorithm and to develop more efficient elastography techniques.

• Proceedings of the Korean Society of Computer Information Conference
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• 2014.01a
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• pp.373-376
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• 2014

최근 모바일 기기 및 무선기기의 발달로 인하여 센서 네트워크가 다양한 분야에서 응용되고 있다. 따라서 센서에서 실시간으로 발생하는 스트리밍 데이터에서 이벤트를 감지하고 분석하는 것은 중요한 연구 분야로 부각되고 있다. 단순 이벤트의 발생 조건을 빠르게 판별하기 위해 비트맵 인덱스 기반 복합 이벤트 검출 기법 등 여러 가지 방법들이 사용되고 있지만, 아직까지 이기종 센서에서 발생하는 각기 다른 형태의 데이터를 융합하여 이벤트를 검출하는 복합 이벤트 처리에 대한 연구는 미비한 실정이다. 본 논문에서는 각기 다른 형태를 가지는 스트리밍 데이터에 멤버쉽 함수를 적용하여 퍼지화 함으로서 이기종 센서에서 발생하는 데이터를 융합 처리가능하며, Quine-Mccluskey 감축기법을 통하여 규칙의 신뢰도 및 속도가 향상된 의사결정을 하는 고속 이벤트 탐지기법을 제안한다.

• Journal of Korean society of Dental Hygiene
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• v.23 no.4
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• pp.235-243
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• 2023

Objectives: This study compared the number of graduates in each region for the past 6 years and the number of dental hygienists working in dental clinics by region to evaluate the trend of dental hygienists moving to work areas after graduation. Methods: Health care big data open system_medical manpower statistics, resident population and household status data by year, and education statistics service were used to calculate the number of dentists and dental hygienists, admission status by region, number of dental hygienists per 100,000 population, number of dental hygienists per number of dentists, and distribution of dental hygienists by region. Results: Although the number of active dental hygienists increased in the metropolitan area, the ratio of dental hygienists to dentists did not improve significantly. In addition, the number of students enrolled in provincial universities decreased, and there were fewer active dental hygienists than graduates in provincial areas. Conclusions: Although the number of active dental hygienists increased due to increase in the number of dental hygiene departments, it was found that rural areas did not have a significant impact on the availability of dental hygienists as the graduates moved to the metropolitan area.