• Title/Summary/Keyword: Medical Big data

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Current Status of Clinical Study on Traditional East Asian Medicine Using Taiwan Health Insurance Claim Data (대만 건강보험청구데이터(NHIRD)를 이용한 전통 동아시아 의학(TEAM) 임상연구의 현황)

  • Jeung, Chang-Woon;Jo, Hee-Geun;Seol, Jae-Uk
    • Journal of Korean Medicine Rehabilitation
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    • v.27 no.2
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    • pp.67-75
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    • 2017
  • Objectives The study of the clinical effects of traditional east asian medicine (TEAM) using Taiwan national health insurance claim dataset (NHIRD) is useful in Korean Medicine research. We reviewed the clinical studies of TEAM using NHIRD as a whole through this study. Methods We comprehensively searched PUBMED and NHIRD DB for clinical effects of TEAM study using NHIRD from inception to 17, January 2017. As a result, 40 studies investigating the contribution of TEAM intervention to health benefit have been confirmed. We analyzed publication time, target disease, sample size, outcome measurement and main result of 40 searched studies. Results The number of TEAM studies using NHIRD grdually increasing. The topics of the team study using NHIRD covered a wide range of subjects including cardiovascular disease, tumor, gynecological disease, diabetes and kidney disease. The studies have shown large samples and reported significant effects on severe diseases. Conclusions The results of this study suggest that the study of Korean Medicine using Big data will be useful for decision making related to health care in Korea. However, considering the limited domestic Korean health insurance data, it will be necessary to activate the big data research of Korean Medicine through the establishment of a separate cohort in Korea.

Development of Multidimensional Analysis System for Bio-pathways (바이오 패스웨이 다차원 분석 시스템 개발)

  • Seo, Dongmin;Choi, Yunsoo;Jeon, Sun-Hee;Lee, Min-Ho
    • The Journal of the Korea Contents Association
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    • v.14 no.11
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    • pp.467-475
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    • 2014
  • With the development of genomics, wearable device and IT/NT, a vast amount of bio-medical data are generated recently. Also, healthcare industries based on big-data are booming and big-data technology based on bio-medical data is rising rapidly as a core technology for improving the national health and aged society. A pathway is the biological deep knowledge that represents the relations of dynamics and interaction among proteins, genes and cells by a network. A pathway is wildly being used as an important part of a bio-medical big-data analysis. However, a pathway analysis requires a lot of time and effort because a pathway is very diverse and high volume. Also, multidimensional analysis systems for various pathways are nonexistent even now. In this paper, we proposed a pathway analysis system that collects user interest pathways from KEGG pathway database that supports the most widely used pathways, constructs a network based on a hierarchy structure of pathways and analyzes the relations of dynamics and interaction among pathways by clustering and selecting core pathways from the network. Finally, to verify the superiority of our pathway analysis system, we evaluate the performance of our system in various experiments.

Roles of Health Technology Assessment for Better Health and Universal Health Coverage in Korea (우리나라 보건의료 발전을 위한 의료기술평가의 역할)

  • Lee, Young Sung
    • Health Policy and Management
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    • v.28 no.3
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    • pp.263-271
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    • 2018
  • Health technology assessment (HTA) is defined as multidisciplinary policy analysis to look into the medical, economic, social, and ethical implications of the development, distribution, and use of health technology. Following the recent changes in the social environment, there are increasing needs to improve Korea's healthcare environment by, inter alia, assessing health technologies in an organized, timely manner in accordance with the government's strategies to ensure that citizens' medical expenses are kept at a stable level. Dedicated to HTA and research, the National Evidence-based Healthcare Collaborating Agency (NECA) analyzes and provides grounds on the clinical safety, efficacy, and economic feasibility of health technologies. HTA offers the most suitable grounds for decision making not only by healthcare professionals but also by policy makers and citizens as seen in a case in 2009 where research revealed that glucosamine lacked preventive and treatment effects for osteoarthritis and glucosamine was subsequently excluded from the National Health Insurance's benefit list to stop the insurance scheme from suffering financial losses and citizens from paying unnecessary medical expenses. For the development of HTA in Korea, the NECA will continue exerting itself to accomplish its mission of providing policy support by health technology reassessment, promoting the establishment and use of big data and HTA platforms for public interest, and developing a new value-based HTA system.

A Study on Efficient Memory Management Using Machine Learning Algorithm

  • Park, Beom-Joo;Kang, Min-Soo;Lee, Minho;Jung, Yong Gyu
    • International journal of advanced smart convergence
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    • v.6 no.1
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    • pp.39-43
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    • 2017
  • As the industry grows, the amount of data grows exponentially, and data analysis using these serves as a predictable solution. As data size increases and processing speed increases, it has begun to be applied to new fields by combining artificial intelligence technology as well as simple big data analysis. In this paper, we propose a method to quickly apply a machine learning based algorithm through efficient resource allocation. The proposed algorithm allocates memory for each attribute. Learning Distinct of Attribute and allocating the right memory. In order to compare the performance of the proposed algorithm, we compared it with the existing K-means algorithm. As a result of measuring the execution time, the speed was improved.

A Study on Optimization Model for IoT and IoB based Optimal Medical Care (IoT(Internet of Things)와 IoB(Internet of Body) 기반 적정 의료를 위한 의료 최적화 모델 연구)

  • Park, Sunho;Kim, Young-kil
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2017.05a
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    • pp.551-554
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    • 2017
  • The largest industry in the world is the medical industry, and due to aging and growing demand for well-being, it is necessary to review the competition strategy of the healthcare industry. We will secure competitiveness among medical institutions through the rapid dissemination of ICT convergence, study the intelligence level of digital health care by increasing the capacity of intelligent medical care by combining big data of medical data and artificial intelligence, And to find a countermeasure for constructing a medical optimization model.

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Current status of and trends in post-mastectomy breast reconstruction in Korea

  • Song, Woo Jin;Kang, Sang Gue;Kim, Eun Key;Song, Seung Yong;Lee, Joon Seok;Lee, Jung Ho;Jin, Ung Sik
    • Archives of Plastic Surgery
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    • v.47 no.2
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    • pp.118-125
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    • 2020
  • Since April 2015, post-mastectomy breast reconstruction has been covered by the Korean National Health Insurance Service (NHIS). The frequency of these procedures has increased very rapidly. We analyzed data obtained from the Big Data Hub of the Health Insurance Review and Assessment Service (HIRA) and determined annual changes in the number of breast reconstruction procedures and related trends in Korea. We evaluated the numbers of mastectomy and breast reconstruction procedures performed between April 2015 and December 2018 using data from the HIRA Big Data Hub. We determined annual changes in the numbers of total, autologous, and implant breast reconstructions after NHIS coverage commenced. Data were analyzed using Microsoft Excel. The post-mastectomy breast reconstruction rate increased from 19.4% in 2015 to 53.4% in 2018. In 2015, implant reconstruction was performed in 1,366 cases and autologous reconstruction in 905 (60.1% and 39.8%, respectively); these figures increased to 3,703 and 1,570 (70.2% and 29.7%, respectively) in 2018. Free tissue transfer and deep inferior epigastric perforator flap creation were the most common autologous reconstruction procedures. For implant-based reconstructions, the rates of directto-implant and tissue-expander breast reconstructions (first stage) were similar in 2018. This study summarizes breast reconstruction trends in Korea after NHIS coverage was expanded in 2015. A significant increase over time in the post-mastectomy breast reconstruction rate was evident, with a trend toward implant-based reconstruction. Analysis of data from the HIRA Big Data Hub can be used to predict breast reconstruction trends and convey precise information to patients and physicians.

Development of Medical Herbs Network Multidimensional Analysis System through Literature Analysis on PubMed (PubMed 문헌 분석을 통한 한약재 네트워크 다차원 분석 시스템 개발)

  • Seo, Dongmin;Yu, Seok Jong;Lee, Min-Ho;Yea, Sang-Jun;Kim, Chul
    • The Journal of the Korea Contents Association
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    • v.16 no.6
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    • pp.260-269
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    • 2016
  • With the development of genomics, wearable device and IT/NT, a vast amount of bio-medical data are generated recently. Also, healthcare industries based on big-data are booming and big-data technology based on bio-medical data is rising rapidly as a core technology for improving the national health and aged society. Also, oriental medicine research is focused with modern research technology and validate it's various biochemical effect by combining with molecular biology technology. However there are few searching system for finding biochemical mechanism which is related to major compounds in oriental medicine. Therefore, in this paper, we collected papers related with medical herbs from PubMed and constructed a medical herbs database to store and manage chemical, gene/protein and biological interaction information extracted by a literature analysis on the papers. Also, to supporting a multidimensional analysis on the database, we developed a network analysis system based on a hierarchy structure of chemical, gene/protein and biological interaction information. Finally, we expect this system will be used the major tool to discover various biochemical effect by combining with molecular biology technology.

Precision nutrition: approach for understanding intra-individual biological variation (정밀영양: 개인 간 대사 다양성을 이해하기 위한 접근)

  • Kim, Yangha
    • Journal of Nutrition and Health
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    • v.55 no.1
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    • pp.1-9
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    • 2022
  • In the past few decades, great progress has been made on understanding the interaction between nutrition and health status. But despite this wealth of knowledge, health problems related to nutrition continue to increase. This leads us to postulate that the continuing trend may result from a lack of consideration for intra-individual biological variation on dietary responses. Precision nutrition utilizes personal information such as age, gender, lifestyle, diet intake, environmental exposure, genetic variants, microbiome, and epigenetics to provide better dietary advices and interventions. Recent technological advances in the artificial intelligence, big data analytics, cloud computing, and machine learning, have made it possible to process data on a scale and in ways that were previously impossible. A big data platform is built by collecting numerous parameters such as meal features, medical metadata, lifestyle variation, genome diversity and microbiome composition. Sophisticated techniques based on machine learning algorithm can be used to integrate and interpret multiple factors and provide dietary guidance at a personalized or stratified level. The development of a suitable machine learning algorithm would make it possible to suggest a personalized diet or functional food based on analysis of intra-individual metabolic variation. This novel precision nutrition might become one of the most exciting and promising approaches of improving health conditions, especially in the context of non-communicable disease prevention.

Smart Device based ECG Sensing IoT Applications (스마트 디바이스 기반 ECG 감지 IoT 응용 서비스에 관한 연구)

  • Mariappan, Vinayagam;Lee, Seungyoun;Lee, Junghoon;Lee, Juyoung;Cha, Jaesang
    • Journal of Satellite, Information and Communications
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    • v.11 no.3
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    • pp.18-23
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    • 2016
  • Internet of things (IoT) is revolutionizing in the patient-Centered medical monitoring and management by authorizing the Smartphone application and data analysis with medical centers. The network connectivity is basic requirement to collect the observed human beings' health information from Smartphone to monitor the health from IoT medical devices in personal healthcare. The IoT environment built in Smartphone is very effective and does not demand infrastructure. This paper presents the smart phone deployed personal IoT architecture for Non-Invasive ECG Capturing. The adaptable IoT medical device cum Gateway is used for personal healthcare with big data storage on cloud configuration. In this approach, the Smartphone camera based imaging technique used to extract the personal ECG waveform and forward it to the cloud based big data storage connectivity using IoT architecture. Elaborated algorithm allows for efficient ECG registration directly from face image captured from Smartphone or Tablet camera. The profound technique may have an exceptional value in monitoring personal healthcare after adequate enhancements are introduced.

A Short-Term Projection of the Government Budget in Medical Expenditures using for the Low-income Handicapped (저소득층 장애인 의료비에 대한 정부부담금 추계)

  • 이선자;김미주;장숙랑;이효영
    • Health Policy and Management
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    • v.13 no.2
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    • pp.125-143
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    • 2003
  • This study was conducted to estimate the future government budget in medical expenditures using for the low-income handicapped, because medical expenditures to the low-income handicapped is escalating in these days. It became a big problem not only to the central-government but also to the district-government because they have to subsidize a part of co-payment. This study was designed to project the future government budget using structural model. For the short-term projection, the structural model is stronger than the regression model. The data used for this study were the population projection data based on National Census Data(2000) of the National Statistical Office, the data of Ministry of Health & Welfare, and the data of National Health Insurance Corporation from November 2m to June 2001. The results of the study are summarized as follows: The future government budget in medical expenditures using to the low-income handicapped will be 15-18 billion Won in the year 2003, 16-23 billion Won in 2004, 18-30 billion Won in 2005, 19-38 billion Won in 2006 and 21-49 billion Won in 2007. It is predicted that they would be increasing rapidly. Therefore, the government budget in medical expenditures using for the low-income handicapped must be enlarged.