• Proceedings of the Korean Society of Computer Information Conference
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• 2022.07a
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• pp.367-370
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• 2022

본 연구는 코로나19 발생 전·후 공공의료를 둘러싼 사회적 인식변화를 뉴스빅데이터를 통해 파악하고자 시도되었다. 뉴스빅데이터는 코로나19 확진자가 처음 발생한 2020년 1월을 기준으로 나누었으며, 코로나19 발생 이전(2018년 1월~2019년 12월, 총 24개월) 40,834건과 코로나19가 발병 이후(2020년 1월~2021년 12월, 총 21개월) 61,761건이었다. 수집된 빅데이터는 R 4.1.1 for Windows를 활용하여 단어 빈도 분석, 연관규칙분석을 실시하였다. 연구결과, 코로나19 발생 전후 뉴스기사에서 공공의료를 둘러싼 핵심어를 비교할 때 코로나19 발생 후에 발생 전보다 큰 폭으로 상승한 단어는 '확산'(664%), '대응'(658%), '의사'(518%), '상황'(504%), '공공병원'(486%), '의료진'(455%), '확충'(324%), '인력'(305%), '어려움'(272%), '정부'(247%)순으로 나타났다. 코로나19 발생 전후 공공의료를 둘러싼 키워드의 연관규칙 분석을 통해서 의료의 패러다임이 일자리 산업에서 감염증 대응을 위한 보건의료로 전환되는 것을 알수 있었다.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.46 no.10
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• pp.1-7
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• 2009

Nowadays there are many studies and there's huge development about RFID and WSN which have great developmental potential to many kinds of applications. In particular, the healthcare field is expected to could be securing international competitive power in u-Healthcare and combined medical treatment industry and service. More and more real time application apply RFID and WSN technology to identify, data collect and locate objects. Wide deployment of RFID and WSN will generate an unprecedented volume of primitive data in a short time. Duplication and redundancy of primitive data will affect real time performance of application. Thus, emerging applications must filter primitive data and correlate them for complex pattern detection and transform them to events that provide meaningful, actionable information to end application. In this paper, we design a complex event processing system. This system will process RFID and WSN primitive data and event and perform data transformation. Integrate RFID and WSN system had applied each now in medical treatment through this study and efficient data transmission and management forecast that is possible.

• Proceedings of the Korea Contents Association Conference
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• 2018.05a
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• pp.231-232
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• 2018

본 연구의 목적은 우리나라 17개 광역자치단체의 건강검진 수, 암진단 수, 자원봉사자 모집 수 등의 데이터를 관련 예산과 시설, 장비 수와의 효율성 평가를 위해 DEA분석을 실시하였다. 이를 통해 각 지역별 보건의료와 관련한 효율성을 지역별로 비교할 수 있다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.545-548
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• 2016

Big data is all data generated in the digital environment which has a variety of large and a short life cycle. The amount and type of data are becoming more and more produced on a larger scale, as a smart phone and the internet are popular, and consequently it has been converted into time for users to take advantage and extract only the valuable and useful data from the generated big data. Big data can also be applied to the medical industry and health sectors. It has created the synergy to be fused with ICT such as IoT, smart healthcare, and so on. However, there will be challenges like data security in order securely to use a meaningful and useful vast amounts of data. In this study, we analyze the future prospects of the healthcare, applications and issues of medical big data, and the expected challenges.

• Korea Multimedia Society
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• v.21 no.4
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• pp.21-32
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• 2017

• Korea Information Processing Society Review
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• v.28 no.2
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• pp.34-43
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• 2021

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.1
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• pp.85-90
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• 2023

Data analysis methodology in the healthcare field is shifting from traditional statistics-oriented research methods to predictive research using machine learning. In this study, we survey various machine learning tools, and compare several programming models, which utilize R and Spark, for applying R, a statistical tool widely used in the health care field, to machine learning. In addition, we compare the performance of linear regression model using scala, which is the basic languages of Spark and R. As a result of the experiment, the learning execution time when using SparkR increased by 10 to 20% compared to Scala. Considering the presented performance degradation, SparkR's distributed processing was confirmed as useful in R as the traditional statistical analysis tool that could be used as it is.

• Journal of the Korea Convergence Society
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• v.12 no.1
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• pp.369-377
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• 2021

Augmented reality smart-glass enables healthcare providers to use patient and their care related information without interference of workflow. In addition, augmented reality smart-glass simulation had advantages in improving competency via remote collaboration and real-time information sharing. This study investigated perception and attitude regarding augmented reality smart glass based healthcare simulation on three different groups of healthcare major students, computer major students, developers and faculties. Using convenience sampling method, data were obtained from 95 participants and statistical analysis were performed using SPSS 25.0. Developer and faculty group showed the highest scores, followed by healthcare major students. There was the high expectation on augmented reality smart-glass for skill acquisition and the high performance and big screen were essential features of device. The findings of this study revealed that differences between healthcare and computer major students exist and strategies to reduce those gaps are required to adopt augmented reality smart glass in healthcare settings.

• Journal of the Health Care and Life Science
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• v.11 no.1
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• pp.1-9
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• 2023

The purpose of this study is to derive the roles of health care information managers in response to rapidly changing environments, analyze students' educational needs, and suggest ways to improve the curriculum of universities. A questionnaire was organized and a survey was conducted by deriving the roles of health care information managers based on the competency units presented in previous studies and NCS. As a result, first, it was found that there is a high need to improve medical information support, statistics generation and utilization, and regulation management in the current role. Second, for future roles, the priority of improvement for work process designers, clinical research coordinators, and business change managers was high. Reflecting these students' educational needs, universities need to establish an environmental basis for organic linkage of related subjects and step-by-step analysis and feedback efforts of instructors' training courses.

• Journal of Digital Convergence
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• v.16 no.12
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• pp.533-540
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• 2018

The purpose of this study was to use the data from the Health Insurance Review and Assessment Service to analyze the disagreement in disease coding given by different medical institutions on the same disease of the same patient and provide basic data that could help improve the quality of national public health statistics. 9,976,826 patients' data records from the Health Insurance Review and Assessment Service-National Patient Sample (HIRA-NPS) of 2014 were analyzed. The disagreement in disease coding differed by movement paths for medical institutions; the disagreement rate tended to increase when moving from a medical institution other than public health centers to a public health center and decrease remarkably when moving from a specialized general hospital to another. Therefore, this analysis of disagreement in disease coding among medical institutions suggests the need to supplement the system so that domestic medical institutions can realize consistent disease coding.