• Journal of Korean society of Dental Hygiene
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• v.17 no.5
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• pp.705-719
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• 2017

Objectives: The purpose of this study is to look into the health insurance systems and application in Korea and Japan in order to improve elderly people's quality of life. Their quality of life can be improved by upgrading the long term care systems; and extending treatment and prevention. Methods: This study is to examine long term care systems articles through content analysis in the National Health Insurance Service. Data were collected from the printed Internet and analyzed. Results: A part-time dentist system in elderly care facilities has trouble in taking care of old people's oral health due to both lack of time and operational difficulties. It is urgent to arrange dental experts who can permanently stay in care facilities and to build systems which can be managed periodically and continually. Conclusions: As having staff training for the efficiency and using the manpower in care facilities (care workers), it is necessary to solve the unequal medical service in oral health care for the elderly in Korea.

• The Korean Nurse
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• v.31 no.3
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• pp.62-75
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• 1992

This study was done to suggest basic modifications in the present situation for the family of women in labour which is a separation management method. The study design was a descriptive study. The number of the subjects were 80. they were husbands, mothers in law, and mothers of women in labour who were full term and for whom there were no complications, either for the mother or the fetus. Data collection was done with a structured questionnaire which was analyzed using frequencies. The results were as follows, 1. Most of the subjects(95.0%) wanted to participate in the labour process. 2. The subjects wanted to support the women in labour by way of encouraging(95.0%), consoling (95.0%), listening to(75.0%), praying with(68.8%), hand holding(97.5%), stroking(63.8%), helping with respiration control(50.0%), maintaining relaxation(46.3%), changing position(58.8%), and illustration (58.8 %). 3. The subjects answered that they expected their participation to have the effect of an easier labour course(52.5%), security for the women in labour(95.0%), and providing a better relationship between the women in labour(66.3%) and the new baby(55.0%). 4. The priority of the response as to who is the best supporter was husband, and mother of the women in labour in that order. It can be concluded that nurses maintained a management method which ignored the needs of the families of women in labour. If given consideration is to be given to these subjects, future programs should initiate ways to let the families participate in the labour process.

• The KIPS Transactions:PartC
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• v.17C no.2
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• pp.173-180
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• 2010

Information technology is being applied to the development of ubiquitous healthcare system, which provides both efficient patient care and convenient treatment regardless of patient's location. However, the increasing number of users and medical information give rise to the problem of user management and the infringement of privacy. In order to address this problem we propose a user access scheme based on the RBAC (Role Based Access Control) model. The preceding trust management model for Grid security, FAS(Federation Agent Server), was analyzed and extended to provide supplementary functions for role-based access control in u-Healthcare system. The RBAC model provides efficient user management and access control, but very vulnerable in case when one with valid role tries to leak confidential inner medical information. In order to resolve this problem, a RBAC-WS (Work Status with RBAC) model has been additionally developed which allows only qualified staffs to access the system while on duty. Th proposed RBAC and RBAC-WS model have been merged together and applied to the PACS (Picture Archiving and Communication System).

• Safety and Health at Work
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• v.12 no.3
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• pp.304-310
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• 2021

Background: Healthcare settings have been recognized among the most hazardous places to work. Based on the five categories of occupational hazards that were identified by the ILO and WHO, this study aimed to analyze policy framework relevant to occupational health protection of health workers (HWs) in public health service in China, then discussed how to share the experience of the National Health Service (NHS) England for improvement. Methods: Based on policy learning theories, policy analysis and qualitative interview were used in this study. Results: In the Chinese public health service, at least five laws related to the regulation of occupational health protection for HWs; however, enforcement of relevant laws was separated and multi-centered; the national monitoring system, which targeted to occupational hazards and health outcome for HWs in China, had yet to be developed; the top three priorities were workplace violence, bloodborne pathogens, and musculoskeletal disorders; national strategies included Security Hospital, and Healthy China 2030. In NHS England, three laws were fundamental; several monitoring systems had been set up, including NHS Staff Survey, Commissioning for Quality and Innovation incentive scheme; mental health, musculoskeletal problem, and nutrition disorder and overweight were raised great concern; Health and Safety, and NHS Healthy Workforce Program were critical nationwide strategies. Conclusion: There were several similarities as well as differences between the Chinese public health system and NHS England, which laid foundation of learning by China. Recommendations of improving occupational health policies in China were provided, based on the lessons learned from the NHS England.

• Journal of Radiation Industry
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• v.12 no.4
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• pp.277-285
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• 2018

Patients administered radioisotope for medical purposes are regulated by each country to quarantine them until their body's radioactivity contents decrease below release criteria. To predict the quarantine period and provide it to medical staffs and patients, it is necessary to approach the assessment of the exposure dose of persons due to patients in a realistic manner. For this purpose, a whole-body effective half-life should be applied to the dose assessment equation instead of the physical half-life. In this study, we constructed a bio-kinetic model for each nuclear species based on the ICRP publication to obtain a whole-body effective half-life of 10 unsealed gamma-ray emitting nuclei from the notification of Nuclear Safety and Security Commission, and calculated the effective half-life mathematically by simulating the distribution of the radioisotope administered in the whole body as well as each organ scale. The whole-body effective half-life of $^{198}Au$, $^{67}Ga$, $^{123}I$, $^{111}In$, $^{186}Re$, $^{99m}Tc$, and $^{201}TI$ were 1,93, 2.57, 0.295, 2.805, 1.561, 0.245, and 2.397 days respectively. However, it was found to be undesirable to offer a single value of the effective half-life of $^{125}I$, $^{131}I$, and $^{169}Yb$ because the changes in the effective half-life show no linearity. A bio-kinetic model created for the internal exposure assessment has been shown to be possible to calculate the effective half-life of radioisotopes administered in the patient's body, but subsequent studies of radiolabeled compounds are required as well.

• Tunnel and Underground Space
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• v.29 no.1
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• pp.1-11
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• 2019

This study investigated use cases of machine learning technology in domestic medical, manufacturing, finance, automobile, urban sectors and those in overseas mining industry. Through a literature survey, it was found that the machine learning technology has been widely utilized for developing medical image information system, real-time monitoring and fault diagnosis system, security level of information system, autonomous vehicle and integrated city management system. Until now, the use cases have not found in the domestic mining industry, however, several overseas projects have found that introduce the machine learning technology to the mining industry for improving the productivity and safety of mineral exploration or mine development. In the future, the introduction of the machine learning technology to the mining industry is expected to spread gradually.

• Korea Journal of Hospital Management
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• v.24 no.3
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• pp.1-10
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• 2019

Purpose: The purpose of this study was to investigate determinants of purchasing indemnity private health insurance and its impact on the healthcare utilization among outpatients with chronic disease. Methods: The study analyzed 4,997 chronic ill patients using 2015 Korean Health Panel data. Logistic regression analysis was conducted to analyze the factors affecting the purchase of indemnity private health insurance and multiple regression analysis was conducted to analyze the effect of private health insurance on the number of outpatient visits and outpatient expenditures. Findings: The age, education level, and number of chronic diseases were significant factors affecting the purchasing of indemnity private health insurance among chronic patients. As a result of analyzing the impact of indemnity private health insurance on healthcare utilization, the number of outpatient visits for those who enrolled in the indemnity private health insurance was higher than the number of outpatient visits for those who did not. But there was no statistically significant difference in outpatient medical expenses. Practical Implications: The results of this study shows that indemnity private health insurance may cause inequality in the healthcare utilization of the socially vulnerable. It is necessary to seek ways to strengthen the health security of chronic disease patients and high-risk elderly people who need more healthcare.

• Journal of Industrial Convergence
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• v.18 no.6
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• pp.9-17
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• 2020

COVID19 is causing many fundamental phenomena all over the world. Since January 2020, the number of confirmed medical examinations has increased significantly worldwide, and the medical systems in each country have become paralyzed. South Korea has taken a proactive approach and is doing well, befitting the name K-Peace Prevention. However, it can be said that there is still a lack of awareness of legal and administrative limits. In this study examines the shortcomings and limitations of the laws relevant to the current infectious disease prevention and management systems from the perspective of criminal policy based on the "Infectious Disease Control and Prevention Act," and comparatively analyzes the laws in advanced countries to propose effective and practical criminal policy response measures for the prevention and control of infectious diseases.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.279-282
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• 2022

Acute lymphoblastic leukemia is an acute leukemia caused by suppression of bone marrow function due to overgrowth of immature lymphocytes in the bone marrow. It accounts for 30% of acute leukemia in adults, and children show a cure rate of over 80% with chemotherapy, while adults show a low survival rate of 20% to 50%. However, research on a machine learning algorithm based on medical image data for the diagnosis of acute lymphoblastic leukemia is in the initial stage. In this paper, we compare and analyze CNN algorithm models for quick and accurate diagnosis. Using four models, an experimental environment for comparative analysis of acute lymphoblastic leukemia diagnostic models was established, and the algorithm with the best accuracy was selected for the given medical image data. According to the experimental results, among the four CNN models, the InceptionV3 model showed the best performance with an accuracy of 98.9%.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.3
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• pp.958-979
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• 2023

Due to laws, regulations, privacy, etc., between 70-90 percent of providers do not share medical data, forming a "data island". It is essential to collaborate across multiple institutions without sharing patient data. Most existing methods adopt distributed learning and centralized federal architecture to solve this problem, but there are problems of resource heterogeneity and data heterogeneity in the practical application process. This paper proposes a collaborative deep learning modelling method based on the blockchain network. The training process uses encryption parameters to replace the original remote source data transmission to protect privacy. Hyperledger Fabric blockchain is adopted to realize that the parties are not restricted by the third-party authoritative verification end. To a certain extent, the distrust and single point of failure caused by the centralized system are avoided. The aggregation algorithm uses the FedProx algorithm to solve the problem of device heterogeneity and data heterogeneity. The experiments show that the maximum improvement of segmentation accuracy in the collaborative training mode proposed in this paper is 11.179% compared to local training. In the sequential training mode, the average accuracy improvement is greater than 7%. In the parallel training mode, the average accuracy improvement is greater than 8%. The experimental results show that the model proposed in this paper can solve the current problem of centralized modelling of multicenter data. In particular, it provides ideas to solve privacy protection and break "data silos", and protects all data.