• Title/Summary/Keyword: Healthcare big data

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Development of Customized 3D Characters for Growth Management and Prediction of Adolescents Using Big Data (빅데이터를 활용한 청소년 성장관리와 예측을 위한 맞춤형 3D 캐릭터 개발 연구)

  • Choo, Hye-Jin;Ha, Seo-Ho
    • The Journal of the Korea Contents Association
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    • v.18 no.1
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    • pp.250-257
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    • 2018
  • Today, the integration of the rapid development of ICT and the smart devices moves our lives quickly into an online community environment through not only quick and easy information search but also various social media. Accordingly, individual activities in the smart media environment are pouring out vast quantities of data in many fields, accumulating a tremendous amount of data. The everyday data of individuals is reproducing different values from the previous ones, while suggesting new customized services that utilize them in various fields. Recently, big data utilization has attracted a great attention in the field of healthcare. Especially, development of healthcare service linked with mobile is expected to bring a new paradigm in this field. In this study, creation of a 3D avatar character model as a means to transfer information to individuals more efficiently is proposed in the development of mobile customized service for health promotion and growth prediction of children and adolescents, at the same time, an effective visual expression method to have a sense of immersion and unity is searched.

Big Query execution for FHIR objects on Google Cloud (구글 클라우드 FHIR 객체의 Big Query 수행)

  • Soyeon Kim;Minchae Kim;Jooeun Jin;Nayeon Kim;Junghoon Lee
    • Proceedings of the Korea Information Processing Society Conference
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    • 2023.11a
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    • pp.269-270
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    • 2023
  • 본 논문에서는 구글 클라우드에 1차적으로 저장된 Healthcare API 서비스의 FHIR 객체들을 Big Query 서비스로 전환하고 질의를 작성하여 결과를 확인하는 과정을 설명한다. 이 과정에서 IAM을 위한 Big Query 테이블로의 입력 권한 부여 과정과 중첩된 필드들을 포함하고 있는 FHIR 객체의 명세과정이 핵심적인 단계가 되고 있으며 위 서비스들의 연계에 의해 대용량의 의료정보들이 구글 클라우드 상에 저장되고 사전분석되어 추가적인 정밀 분석을 위한 기저 자료를 제공할 수 있다.

Research Trend Analysis by using Text-Mining Techniques on the Convergence Studies of AI and Healthcare Technologies (텍스트 마이닝 기법을 활용한 인공지능과 헬스케어 융·복합 분야 연구동향 분석)

  • Yoon, Jee-Eun;Suh, Chang-Jin
    • Journal of Information Technology Services
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    • v.18 no.2
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    • pp.123-141
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    • 2019
  • The goal of this study is to review the major research trend on the convergence studies of AI and healthcare technologies. For the study, 15,260 English articles on AI and healthcare related topics were collected from Scopus for 55 years from 1963, and text mining techniques were conducted. As a result, seven key research topics were defined : "AI for Clinical Decision Support System (CDSS)", "AI for Medical Image", "Internet of Healthcare Things (IoHT)", "Big Data Analytics in Healthcare", "Medical Robotics", "Blockchain in Healthcare", and "Evidence Based Medicine (EBM)". The result of this study can be utilized to set up and develop the appropriate healthcare R&D strategies for the researchers and government. In this study, text mining techniques such as Text Analysis, Frequency Analysis, Topic Modeling on LDA (Latent Dirichlet Allocation), Word Cloud, and Ego Network Analysis were conducted.

The Effect of Data 3 on the Utilization of Medical Big Data for Early Detection of Dementia (데이터 3법이 치매 조기 예측을 위한 의료 빅데이터 활용에 미치는 영향 연구)

  • Kim, Hyejin
    • Journal of Digital Convergence
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    • v.18 no.5
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    • pp.305-315
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    • 2020
  • As the incidence and prevalence of dementia increases with our aging population, so does the social burden on our society, which calls for a special emphasis on need for early diagnosis. Thus, efforts are made to prevent dementia and early detection but with current diagnostic measures, these efforts appear futile. As a solution, it is crucial to integrate and standardize healthcare big data and analysis of each index. In order to increase use of large database, the Korea National Assembly passed the Data 3 Act focusing on open-access and sharing of database, but a follow-up legislation is needed a for safer utilization. In this study, we have identified number of foreign of foreign policies through review of prior researches on the topic leading to specific enforcement ordinances tailored to the Data 3 Act for safe access and utilization of database. We also aimed to establish secure process of data collection and disposal as well as governance at the national level to ensure safe utilization of healthcare big data.

Research Trends on Healthcare Wearables Published in Korean Journals

  • Kim, Nam Soon;Do, Wol Hee
    • Fashion & Textile Research Journal
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    • v.22 no.5
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    • pp.607-616
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    • 2020
  • Health care wearables are devices that are attached to or combined with the human body to improve the health care capabilities of the human body that can be safely and adjustable according to preference. This study provided direction for future research on healthcare wearables in the field of clothing science, considering trends observed in this field from 2010 to 2019. Over the last 10 years, 812 studies have been conducted on healthcare wearables in Korea. Research has increased significantly since 2015, with a large number of articles published in this field. The research for this study was broken down into the following categories: technology development, marketing analysis, and technology analysis. The results according to the research method demonstrated that development and production methods were used most frequently, followed by trend analysis, experiment and evaluation, and survey. An analysis of keywords in the articles studied revealed that device, healthcare, big data (biometric data and database), and healthcare convergence technologies were trending. Similarly, detailed research on healthcare wearable devices and related technologies was actively being conducted. However, focusing on fiber, textiles, design, and clothing articles, in relation to the field of clothing in healthcare wearables, only 81 articles were found on this topic (10.0%), which was low compared to other studies. Therefore, it was determined that more research on healthcare wearables is necessary in the field of clothing.

The Management of Medical Information Quality Utilizing Big Data (빅 데이터를 활용한 의료정보 질 관리)

  • Cho, Young-bok;Woo, Sung-Hee;Lee, Sang-Ho
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2014.05a
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    • pp.728-731
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    • 2014
  • Today, the quality of medical service has become a major concern because that sustainable development of IT technology and extending people's life expectancy. This paper, it is used as a tool for the medical information quality management that analyze tweets big data form generated by individual's daily. The result of the analyze big data offers improvement medical information based evidence based medicine. Also it has been possible for a trace observation of chronic disease and can reduce additional other complications of patients. Therefore, effective treatment of disease and prevention is possible.

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Heterogeneous Lifelog Mining Model in Health Big-data Platform (헬스 빅데이터 플랫폼에서 이기종 라이프로그 마이닝 모델)

  • Kang, JI-Soo;Chung, Kyungyong
    • Journal of the Korea Convergence Society
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    • v.9 no.10
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    • pp.75-80
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    • 2018
  • In this paper, we propose heterogeneous lifelog mining model in health big-data platform. It is an ontology-based mining model for collecting user's lifelog in real-time and providing healthcare services. The proposed method distributes heterogeneous lifelog data and processes it in real time in a cloud computing environment. The knowledge base is reconstructed by an upper ontology method suitable for the environment constructed based on the heterogeneous ontology. The restructured knowledge base generates inference rules using Jena 4.0 inference engines, and provides real-time healthcare services by rule-based inference methods. Lifelog mining constructs an analysis of hidden relationships and a predictive model for time-series bio-signal. This enables real-time healthcare services that realize preventive health services to detect changes in the users' bio-signal by exploring negative or positive correlations that are not included in the relationships or inference rules. The performance evaluation shows that the proposed heterogeneous lifelog mining model method is superior to other models with an accuracy of 0.734, a precision of 0.752.

Data Linkage Method Using LOD in the Healthcare Big Data Platform (보건의료 빅데이터 플랫폼에서 LOD를 활용한 데이터 연계 방안)

  • Lee, Kyung-Hee;Kim, Kinam;Cho, Wan-Sup
    • The Journal of Bigdata
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    • v.4 no.2
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    • pp.195-205
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    • 2019
  • Linked Open Data (LOD) is rated as the best of any kind of data disclosure, and allows you to search related data by linking them in a standard format across the Internet. There is an increasing number of cases in which relevant data are constructed in the LOD form in the global environment, but in the domestic healthcare sector, the disclosure of data in the form of LOD is still at the beginning stage. In this paper, we introduce a case of LOD platform construction that provides services by linking domestic and international related data by LOD method, based on the data of Korean medical research paper data and health care big data linkage platform. Linking all data from each DB into an LOD requires a lot of time and effort, and is basically an infrastructure task that government or public institutions should be in charge of rather than the private sector. In this study, ten domestic and foreign LOD sites were linked with only a portion of each DB, enabling users to link data from various domestic and foreign organizations in a convenient manner.

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Big Data Processing and Utilization (빅데이터 처리 프로세스 및 활용)

  • Lee, Seong-Hoon;Lee, Dong-Woo
    • Journal of Digital Convergence
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    • v.11 no.4
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    • pp.267-271
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    • 2013
  • Our society has two prospective properties because of IT technology. Firstly, it is accelerated a degree of convergence. And convergence regions are expanded. For example, smart healthcare region was created by IT technology and medical industry. The efforts to convergence will be continued. Because of these properties, A number of data are made in our life. Through many devices such as smart phone, camera, game machine, tablet pc, various data types are produced. In this paper, we described utilization of Big Data. And we analysed Big Data processing process.

A Study on the Technological Priorities of Manufacturing and Service Companies for Response to the 4th Industrial Revolution and Transformation into a Smart Company (4차 산업혁명 대응과 스마트 기업으로의 변화를 위한 제조 및 서비스 기업의 기술적용 우선순위에 대한 연구)

  • Park, Chan-Kwon;Seo, Yeong-Bok
    • Journal of Convergence for Information Technology
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    • v.11 no.4
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    • pp.83-101
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    • 2021
  • This study is to investigate, using AHP, what technologies should be applied first to Korean SMEs in order to respond to the 4th industrial revolution and change to a smart enterprise. To this end, technologies related to the 4th industrial revolution and smart factory are synthesized, and the classification criteria of Dae-Hoon Kim et al. (2019) are applied, but additional opinions of experts are collected and related technologies are converted to artificial intelligence (AI), Big Data, and Cloud Computing. As a base technology, mobile, Internet of Things (IoT), block chain as hyper-connected technology, unmanned transportation (autonomous driving), robot, 3D printing, drone as a convergence technology, smart manufacturing and logistics, smart healthcare, smart transportation and smart finance were classified as smart industrial technologies. As a result of confirming the priorities for technical use by AHP analysis and calculating the total weight, manufacturing companies have a high ranking in mobile, artificial intelligence (AI), big data, and robots, while service companies are in big data and robots, artificial intelligence (AI), and smart healthcare are ranked high, and in all companies, it is in the order of big data, artificial intelligence (AI), robot, and mobile. Through this study, it was clearly identified which technologies should be applied first in order to respond to the 4th industrial revolution and change to a smart company.