• Radiation Oncology Journal
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• v.37 no.4
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• pp.249-253
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• 2019

Purpose: We aimed to analyze the trend in intensity-modulated radiation therapy (IMRT) use in Korea from 2011 to 2018. Materials and Methods: We collected data from the Health and Insurance Review and Assessment Service (HIRA) big data based on the National Health Insurance Service claims and reimbursements records using primary treatment planning codes (HD 041) for IMRT from 2011 to 2018. We analyzed the changing patterns in clinical application to specific tumor sites and regional differences in IMRT utilization. Results: The use of IMRT has exhibited an 18-fold steep rise from 1,921 patients in 2011 to 34,759 in 2018. With regard to IMRT in 2018, 70% of patients (24,248/34,759) were treated in metropolitan areas (Seoul, Incheon, and Gyeonggi Province). IMRT was most commonly used to treat breast, lung, and prostate cancers in 2018. Among these, the use of IMRT for breast cancer shows the most remarkable increase from 2016 when the National Health Insurance began to cover IMRT for all solid tumors. Conclusion: The use of IMRT is steadily increasing to treat cancer and is concentrated in metropolitan areas.

• Korea Journal of Hospital Management
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• v.23 no.3
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• pp.52-62
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• 2018

This study aims to analyze the factors affecting in-hospital complication and length of stay in elderly patients with total knee arthroplasty. A total of 8,224 inpatients over 65 years old were selected from the national old inpatient sample data which was produced by Health Insurance Review and Assessment Service in 2016. STATA 12.0 was performed using frequency, chi-square test, t-test, ANOVA and multiple linear and logistic regression analysis. Analysis results show that ages(over 85), Charlson Comorbidity Index, district(metropolitan) for general hospitals and gender, district, beds(100-199) for hospitals are significantly influenced in-hospital complication. Statistically significant factors affecting the length of stay are gender, insurance type, depression, district, bed(300 over) for general hospitals and gender, type of insurance, Charlson Comorbidity Index, depression, district, beds(200-299) for hospitals. Based on these findings, the factors affecting in-hospital complication and length of stay were different depending on the type of medical institution. Accordingly, policymakers should analyze the differences in care behavior depending on the type of medical institution and expand policy and financial support to resolve them.

• Journal of Korean society of Dental Hygiene
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• v.21 no.1
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• pp.27-40
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• 2021

Objectives: This study investigated the working conditions of dental hygienists and their challenges in providing oral care to older adults with dementia using focus group interviews. Methods: We collected data for approximately a month beginning from August 2020 and divided the study subjects into two groups: the health dental hygienist and the clinical dental hygienist groups. A total of 11 subjects participated in this study. Results: The oral health management of older adult patients with dementia has not been efficiently carried out in local communities or dental medical institutions. In addition, dental hygienists encounter difficulties in managing the oral health of these patients and hope to actively learn more about their special cases. Conclusions: Based on the results of this study, it is necessary to develop a manual or program for the professional implementation of oral health interventions for older adults with dementia.

• Journal of Korean Academy of Nursing
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• v.53 no.4
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• pp.439-452
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• 2023

Purpose: This study aimed to derive considerations for the enactment of nursing law by analyzing the trends and social perceptions of nursing law mentioned in major daily newspapers, cafes, and blogs. Methods: Main texts and comments that included nursing law as a keyword were collected from major daily news and online postings from January 2021 to August 2022. The data collected through web crawling were analyzed using a TousFlux program used for big data analysis. Results: During the period of study, the awareness level around nursing law enactment increased. In particular, public concern over nursing law enactment intensified due to the two political parties' policy pledges related to nursing law in January 2022 and the failure to introduce the nursing law to the national assembly judiciary committee in May 2022. Except in December 2021, public perception of nursing law enactment was generally favorable, with public opinion tilting more in favor of than against enactment. Conclusion: Public opinion should be considered when drafting and implementing the nursing law to make it easier for the people to understand what the law constitutes. In addition, it is necessary to pay attention to and continuously promote the relationship between medical care and nursing in the nursing law system of developed nations. Lastly, nursing law enactment can enhance nurses' retention intention and provide a sense of efficacy to medical services.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.517-519
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• 2022

VR based dementia service is emerged as elderly population is increasing with potential welfare cost. Current Dementia Center cannot solve the complicated problems, including limited size, case management, medical support, medical cost and care cost, and the lack preventive environment. VR based dementia service is suggested from three reasons: First, VR shows easy access and convenience; Second, development of cognitive health is easy and fun; Third, Predictive way of cognitive decline can be possible with Big Data.

• Journal of Dental Anesthesia and Pain Medicine
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• v.22 no.3
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• pp.205-216
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• 2022

Background: People with special needs tend to require diverse behavioral management in dentistry. They may feel anxious or uncomfortable or may not respond to any communication with the dentists. Patients with medical, physical, or psychological disorders may not cooperate and therefore require sedation (SED) or general anesthesia (GA) to receive dental treatment. Using the healthcare big data in Korea, this study aimed to analyze the trends of SED and GA in special needs patients undergoing dental treatment. It is believed that these data can be used as reference material for hospitals and for preparation of guidelines and related policy decisions of associations or governments for special needs patients in dentistry. Methods: The study used selected health information data provided by the Korean National Health Insurance Service. Patients with a record of use of one of the eight selected drugs used in dental SED between January 2007 and September 2019, those with International Classification of Diseases-10 codes for attention deficit hyperactivity disorder (ADHD), phobia, brain disease, cerebral palsy, epilepsy, genetic disease, autism, mental disorder, mental retardation, and dementia were selected. The insurance claims data were analyzed for age, sex, sedative use, GA, year, and institution. Results: The number of special needs patients who received dental treatment under SED or GA from January 2007 to September 2019 was 116,623. Number of SED cases was 136,018, performed on 69,265 patients, and the number of GA cases was 56,308, implemented on 47,257 patients. In 2007, 3100 special needs patients received dental treatment under SED while in 2018 the number of cases increased 6 times to 18,528 SED cases. In dentistry, ADHD was the most common disability for SED cases while phobia was the most common cause of disability for GA. The male-to-female ratio with respect to SED cases was higher for males (M : F = 64.36% : 35.64%). Conclusion: The application of the SED method and GA for patients with special needs in dentistry is increasing rapidly; thus, preparing guidelines and reinforcing the education and system are necessary.

• Journal of Ginseng Research
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• v.45 no.2
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• pp.334-343
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• 2021

Background: Gut microbiota mainly function in the biotransformation of primary ginsenosides into bioactive metabolites. Herein, we investigated the effects of three prebiotic fibers by targeting gut microbiota on the metabolism of ginsenoside Rb1 in vivo. Methods: Sprague Dawley rats were administered with ginsenoside Rb1 after a two-week prebiotic intervention of fructooligosaccharide, galactooligosaccharide, and fibersol-2, respectively. Pharmacokinetic analysis of ginsenoside Rb1 and its metabolites was performed, whilst the microbial composition and metabolic function of gut microbiota were examined by 16S rRNA gene amplicon and metagenomic shotgun sequencing. Results: The results showed that peak plasma concentration and area under concentration time curve of ginsenoside Rb1 and its intermediate metabolites, ginsenoside Rd, F2, and compound K (CK), in the prebiotic intervention groups were increased at various degrees compared with those in the control group. Gut microbiota dramatically responded to the prebiotic treatment at both taxonomical and functional levels. The abundance of Prevotella, which possesses potential function to hydrolyze ginsenoside Rb1 into CK, was significantly elevated in the three prebiotic groups (P < 0.05). The gut metagenomic analysis also revealed the functional gene enrichment for terpenoid/polyketide metabolism, glycolysis, gluconeogenesis, propanoate metabolism, etc. Conclusion: These findings imply that prebiotics may selectively promote the proliferation of certain bacterial stains with glycoside hydrolysis capacity, thereby, subsequently improving the biotransformation and bioavailability of primary ginsenosides in vivo.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.16 no.2
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• pp.111-118
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• 2016

Artificial intelligence (AI) is making computer systems intelligent to do right thing. The AI is used today in a variety of fields, such as journalism, medical, industry as well as entertainment. The impact of AI is becoming larger day after day. In general, the AI system has to lead the optimal decision under uncertainty. But it is difficult for the AI system can derive the best conclusion. In addition, we have a trouble to represent the intelligent capacity of AI in numeric values. Statistics has the ability to quantify the uncertainty by two approaches of frequentist and Bayesian. So in this paper, we propose a methodology of the connection between statistics and AI efficiently. We compute a fixed value for estimating the population parameter using the frequentist learning. Also we find a probability distribution to estimate the parameter of conceptual population using Bayesian learning. To show how our proposed research could be applied to practical domain, we collect the patent big data related to Apple company, and we make the AI more intelligent to understand Apple's technology.

• The Korean Journal of Physiology and Pharmacology
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• v.23 no.5
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• pp.311-315
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• 2019

Recently, digital health has gained the attention of physicians, patients, and healthcare industries. Digital health, a broad umbrella term, can be defined as an emerging health area that uses brand new digital or medical technologies involving genomics, big data, wearables, mobile applications, and artificial intelligence. Digital health has been highlighted as a way of realizing precision medicine, and in addition is expected to become synonymous with health itself with the rapid digitization of all health-related data. In this article, we first define digital health by reviewing the diverse range of definitions among academia and government agencies. Based on these definitions, we then review the current status of digital health, mainly in Korea, suggest points that are missing from the discussion or ought to be added, and provide future directions of digital health in clinical practice by pointing out certain key points.

• Journal of the Korean Society of Industry Convergence
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• v.26 no.5
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• pp.785-792
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• 2023

Because hyperspectral imaging provides detailed spectral information across a broad range of wavelengths, it can be utilized in numerous applications, including environmental monitoring, food quality inspection, medical diagnosis, material identification, art authentication, and crime scene analysis. However, hyperspectral images often contain various types of distortions due to the environmental conditions during image acquisition, which necessitates the proper removal of these distortions through a data preprocessing process. In this study, a preprocessing method was investigated to effectively correct the distortion caused by artificial light sources used in indoor hyperspectral imaging. For this purpose, a halogen-tungsten artificial light source was installed indoors, and hyperspectral images were acquired. The acquired images were then corrected for distortion using a preprocessing that does not require complex auxiliary equipment. After the corrections were made, the results were analyzed. According to the analysis, a statistical transformation technique using mean and standard deviation with reference to a reference signal was found to be the most effective in correcting distortions caused by artificial light sources.