• Title/Summary/Keyword: Healthcare information systems

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Smart healthcare policy trends using IoT technology (IoT 기술을 활용한 스마트헬스케어 정책 동향)

  • Choi, Hun;Choi, YooJung
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2017.05a
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    • pp.215-216
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    • 2017
  • In recent years, the quality of our lives has been improved by providing services that utilize IoT(Internet of Things) technology in various fields. The information obtained through IoT technology provides a basis for actively providing services that people want. However, in the field of smart healthcare, there are a lot of restrictions due to legal regulations and policies due to the scope of handling not only personal information but also simple medical information. Therefore, this study examines the legal systems and policies in the field of smart healthcare and examines the direction of smart healthcare.

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Cyber-Physical Computing: Leveraging Cloud computing for Ubiquitous Healthcare Applications (사이버 물리 컴퓨팅 : 유비쿼터스 건강 관리 응용에 대한 레버리징 클라우드컴퓨팅)

  • Abid, Hassan;Jin, Wang;Lee, Sung-Young;Lee, Young-Koo
    • Proceedings of the Korean Information Science Society Conference
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    • 2011.06b
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    • pp.41-43
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    • 2011
  • Cyber-Physical Systems are tight integration of computation, networking and physical objects to sense, monitor, and control the physical world. This paper presents a novel architecture that combines two next generation technologies i.e. cyber-physical systems and Cloud computing to develop a ubiquitous healthcare based infrastructure. Through this infrastructure, patients and elderly people get remote assistance, monitoring of their health conditions and medication while living in proximity of home. Consequently, this leads to major cost savings. However, there are various challenges that need to be overcome before building such systems. These challenges include making system real-time responsive, reliability, stability and privacy. Therefore, in this paper, we propose an architecture that deals with these challenges.

The review of qualifying systems of quality improvement specialists in healthcare (의료의 질 개선 전문가의 자격 시스템에 대한 현황)

  • Park, Seong-Hi;Hwang, Jeong-Hae;Choi, Yun-Kyoung;Lee, Sun-Gyo
    • Quality Improvement in Health Care
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    • v.19 no.2
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    • pp.14-34
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    • 2013
  • Objectives: The purpose of this study is to provide comprehensive information of qualification systems of developed countries needed to establish our national system for QI(Quality improvement) specialists. Methods: All articles related to any applicable domestic or foreign countries' laws, operational status, and detailed programs for professional qualification system of QI were reviewed. Result: In the United States, a non-profit organization, Healthcare Quality Certification Commission (HQCC) has set the policies, procedures and standards in the field of health care quality. And qualification system of CPHQ (certified professional in healthcare quality) has been operated in order to authenticate the qualifications in the field of quality management. IBQH(international Board for quality in healthcare), a qualification system of experts in the United Kingdom, was designed to assist the qualification of professionals to improve the quality of healthcare. In addition, Health Research Center of Feinberg School of Medicine in Northwestern University has been operating Master's and doctoral degree programs in the field of the quality of care and patient safety and IHI (institute for healthcare improvement) open school was operating a professional training course related to the quality of care and patient safety. Conclusion: Quantity and complexity of information of the quality of care and patient safety have been increased. For reform of the health care system, a special training course of the expertise and leadership are needed. So far, there is no national professional certification courses in our nation. Therefore essential job skill should be acquired individually. For systematic and effective quality improvement activities, the educational and certification system with professional development model are needed.

바이오 센서 및 랩온어칩

  • 박유근
    • The Magazine of the IEIE
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    • v.31 no.1
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    • pp.58-72
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    • 2004
  • Smart sensors and biochip technologies have received a great deal of attention in recent years not only because of the enormous potential markets in the healthcare expenditures but more importantly because of its great impact on the quality of human life in the future. Collaborative research among BT (Bio Technologies), IT (Information Technologies) and NT (Nano Technologies) will bring us a new paradigm of the healthcare services. Examples include disease prediction based on the genetic tests, personal medicines, point-of-care analysis, rapid and sensitive infectious disease diagnostics, environmental monitoring for chemical or biological warfares, intelligent drug delivery systems etc. In this report, recent accomplishment in the research area on biosensors, DNA chips, Protein Chips and Lab-on-a-chips are reviewed.

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Development of Classification Model for Healthcare Contents on the Online Community (온라인 커뮤니티에서의 건강 관련 콘텐츠 분류 모형 개발)

  • Kim, Tae-Yun;Kim, Yoo-Sin;Choi, Sang-Hyun;Kim, Do-Hun;Chang, You-Jin
    • The Journal of Information Systems
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    • v.26 no.4
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    • pp.285-301
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    • 2017
  • Purpose In this paper we verified the reliabilities of healthcare-related information provided by various users on the site of Naver Jisikin, a Korean typical search platform. Based on Q&A contents we validated answers' reliabilities to the asked questions about a lung cancer with the help of professors at a medical school. Design/methodology/approach The content analysis includes that the types of questions are classified into symptom/diagnosis, therapy, prognosis, after-management and so on. The answers contains advice, advertisement, oriental medicine, and religion as well as the above 5 question categories. The validation results of medical evidence about each answer show that only 49% among all answers have medical grounds. Findings We classified the medical grounded answers into three levels; high, medium and low. Among all answers we need to find out the answers including advertisement because the answers can be harmful to patients. We found the method to select the answers containing advertisement contents with the help of text mining research. The selection model presents high performance as 84% classification accuracy.

SVC: Secure VANET-Assisted Remote Healthcare Monitoring System in Disaster Area

  • Liu, Xuefeng;Quan, Hanyu;Zhang, Yuqing;Zhao, Qianqian;Liu, Ling
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.10 no.3
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    • pp.1229-1248
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    • 2016
  • With the feature of convenience and low cost, remote healthcare monitoring (RHM) has been extensively used in modern disease management to improve the quality of life. Due to the privacy of health data, it is of great importance to implement RHM based on a secure and dependable network. However, the network connectivity of existing RHM systems is unreliable in disaster area because of the unforeseeable damage to the communication infrastructure. To design a secure RHM system in disaster area, this paper presents a Secure VANET-Assisted Remote Healthcare Monitoring System (SVC) by utilizing the unique "store-carry-forward" transmission mode of vehicular ad hoc network (VANET). To improve the network performance, the VANET in SVC is designed to be a two-level network consisting of two kinds of vehicles. Specially, an innovative two-level key management model by mixing certificate-based cryptography and ID-based cryptography is customized to manage the trust of vehicles. In addition, the strong privacy of the health information including context privacy is taken into account in our scheme by combining searchable public-key encryption and broadcast techniques. Finally, comprehensive security and performance analysis demonstrate the scheme is secure and efficient.

Cooperative and Competitive Effect in Heterogeneous Networks of Healthcare System

  • Liu, Xiaoshuang;Kang, Guixia;Zhang, Ningbo;Guo, Yanyan
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.9 no.11
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    • pp.4405-4418
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    • 2015
  • Different network provides different service. To maximize the profit, heterogeneous networks form a whole, which may either compete or cooperate with each other. In this paper, the healthcare monitor network architecture is introduced to build the competitive and cooperative mechanisms of heterogeneous networks which contain three networks, namely, cellular network, WLAN and WMAN. This paper considers the natural growth rate of the network with competitive and cooperative effects. Then, the stability of the proposed model and its equilibrium points are analyzed by the ordinary differential principle. Finally, simulation results show that the natural growth rate cannot increase the profit of the network, but effective cooperative among heterogeneous networks can increase the profit of each network, and competitive may decrease the profit of each network.

Multi-Modal Sensing M2M Healthcare Service in WSN

  • Chung, Wan-Young
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.6 no.4
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    • pp.1090-1105
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    • 2012
  • A multi-modal sensing M2M healthcare monitoring system for the continuous monitoring of patients under their natural physiological states or elderly persons with chronic diseases is summarized. The system is designed for homecare or the monitoring of the elderly who live in country side or small rest home without enough support from caregivers or doctors, instead of patient monitoring in big hospital environment. Further insights into the natural cause and progression of diseases are afforded by context-aware sensing, which includes the use of accelerometers to monitor patient activities, or by location-aware indoor tracking based on ultrasonic and RF sensing. Moreover, indoor location tracking provides information about the location of patients in their physical environment and helps the caregiver in the provision of appropriate support.

Hybrid Fraud Detection Model: Detecting Fraudulent Information in the Healthcare Crowdfunding

  • Choi, Jaewon;Kim, Jaehyoun;Lee, Ho
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.16 no.3
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    • pp.1006-1027
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    • 2022
  • In the crowdfunding market, various crowdfunding platforms can offer founders the possibilities to collect funding and launch someone's next campaign, project or events. Especially, healthcare crowdfunding is a field that is growing rapidly on health-related problems based on online platforms. One of the largest platforms, GoFundMe, has raised US$ 5 billion since 2010. Unfortunately, while providing crucial help to care for many people, it is also increasing risk of fraud. Using the largest platform of crowdfunding market, GoFundMe, we conduct an exhaustive search of detection on fraud from October 2016 to September 2019. Data sets are based on 6 main types of medical focused crowdfunding campaigns or events, such as cancer, in vitro fertilization (IVF), leukemia, health insurance, lymphoma and, surgery type. This study evaluated a detect of fraud process to identify fraud from non-fraud healthcare crowdfunding campaigns using various machine learning technics.

IoT-Based Health Big-Data Process Technologies: A Survey

  • Yoo, Hyun;Park, Roy C.;Chung, Kyungyong
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.15 no.3
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    • pp.974-992
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    • 2021
  • Recently, the healthcare field has undergone rapid changes owing to the accumulation of health big data and the development of machine learning. Data mining research in the field of healthcare has different characteristics from those of other data analyses, such as the structural complexity of the medical data, requirement for medical expertise, and security of personal medical information. Various methods have been implemented to address these issues, including the machine learning model and cloud platform. However, the machine learning model presents the problem of opaque result interpretation, and the cloud platform requires more in-depth research on security and efficiency. To address these issues, this paper presents a recent technology for Internet-of-Things-based (IoT-based) health big data processing. We present a cloud-based IoT health platform and health big data processing technology that reduces the medical data management costs and enhances safety. We also present a data mining technology for health-risk prediction, which is the core of healthcare. Finally, we propose a study using explainable artificial intelligence that enhances the reliability and transparency of the decision-making system, which is called the black box model owing to its lack of transparency.