• 보건행정학회지
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• 제20권3호
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• pp.58-72
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• 2010

The purpose of this study is to investigate determinants of intent to use a wireless information technology(WIT) of University Hospital Nurses. The independent variables used in the study are usefulness, compatibility, social environment, perceived readiness, technical readiness, organizational readiness and socio-demographic characteristics. The dependent variable is the intent to use a wireless information technology(WIT). The sample used in this study consisted of 297 nurses selected from a university hospital located in Wonju, Gangwon-do, Korea Data were collected with self-administered questionnaires and analyzed using multiple regression analysis. The results of the study revealed that 5 independent variables of usefulness, compatibility, perceived readiness, technical readiness, and organizational readiness were found to have significant effects on the nurses' intent to use a WIT. As a conclusion, it is important to make organizational, clinical, and technical environment WIT-friendly prior to applying WIT to hospital nurses. In addition, it is also important to provide an education and training for nurses to improve their skill of using WIT and to make the new WIT compatible with the existing nursing information system.

• 보건교육건강증진학회지
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• 제13권1호
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• pp.45-51
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• 1996

The Korea Information Infrastructure aims at the construction of an advanced national information infrastructure, consisting of communication networks, computers, databases and multimedia terminals. In the emerging information society, a well-established national information network plays a crucial role in enhancing economic efficiency and creating national wealth. Till 2015, government plans to construct an Information Superhighway Network and to provide a telecommunication service for speedy transmission of multi-media typed information and development of various applied programs, which help government's commitment to establish nationwide infrastructure to perform a leading role as a high level information society in the 21st century. In the field of health education, the research monograph contains three main parts: health education and information, acceptability of health education; development of health education management information system. In the most remote areas, it can bring high-quality health care where none is now available. In global health care, it can enhance and standardize the quality of medical care throughout the world. Before enlarging the establishment of the health education network system, the issues from this study should be considered to improve the health status through the introduction of information technology and applications in health care.

• International Journal of Internet, Broadcasting and Communication
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• 제12권3호
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• pp.149-155
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• 2020

Air pollution is a problem of environmental health risk in big cities. Recently, researchers have proposed using various artificial intelligence technologies to predict air pollution. The proposed model is Cooperative of Artificial Neural Network (ANN) and Fuzzy Inference System (FIS), to predict air pollution of Korean cities using Python. Data air pollutant variables were collected and the Air Korean Web site air quality index was downloaded. This paper's aim was to predict on the health risks and the very unhealthy values of air pollution. We have predicted the air pollution of the environment based on the air quality index. According to the results of the experiment, our model was able to predict a very unhealthy value.

• 한국응급구조학회지
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• 제24권3호
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• pp.29-40
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• 2020

Purpose: This study looked into the reality of the emergency medical technology department by analyzing the major indicators of university information disclosure systems and finding the competitiveness of the department of emergency medical technology by reviewing various evaluation indices. Methods: This study is a survey of 24 colleges with emergency medical technology and emergency medical technology departments across the country. Quantitative index data from 2017 to 2019 were collected and analyzed through the university information disclosure center web site. Results: Departments of emergency medical technology are generally higher than the target colleges in quantitative indicators, but the indices are somewhat insufficient in terms of "rate of faculty in full service" and "research performance of per one faculty in full service." Conclusion: Based on the results of this study, we recommend increasing the low indicators to enhance the competitiveness of the departments of emergency medical technology.

• 보건행정학회지
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• 제28권3호
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• pp.272-279
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• 2018

Since the introduction of new health technology assessment in 2007, benefit coverage process of health insurance related to new health technology has become an upgraded system through the evidence-based decisions. As a result of enforcing this system for 10 years, however, there have been several rising concerns. It needs to support the insufficient evidence of medical technologies, introduce reassessment system for post management of market entry technologies, and improve evaluation methods and process. In addition, there is the possibility of emerging an unheard-of medical technology, fused various categories like artificial intelligence, robot, information technology, physics and life science in the fourth industrial revolution. Now, new updated system introduced to improve new technology assessment, such as 'limited health technology assessment system,' 'system for postponement of new health technology assessment,' 'one-stop service system,' and 'integrated operation of approval for medical devices and new health technology assessment.' Therefore it needs to prepare the improvement plan for new health technology assessment to be established more advanced system, and we have to resolve concerns by communication with various healthcare experts and patients now and for ever.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권3호
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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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제18권2호
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• pp.370-396
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• 2024

COVID-19 was declared a pandemic by the World Health Organization (WHO) on 30 January 2020. The lifestyle of people all over the world has changed since. In most cases, the pandemic has appeared to create severe mental disorders, anxieties, and depression among people. Mostly, the researchers have been conducting surveys to identify the impacts of the pandemic on the mental health of people. Despite the better quality, tailored, and more specific data that can be generated by surveys,social media offers great insights into revealing the impact of the pandemic on mental health. Since people feel connected on social media, thus, this study aims to get the people's sentiments about the pandemic related to mental issues. Word Cloud was used to visualize and identify the most frequent keywords related to COVID-19 and mental health disorders. This study employs Majority Voting Ensemble (MVE) classification and individual classifiers such as Naïve Bayes (NB), Support Vector Machine (SVM), and Logistic Regression (LR) to classify the sentiment through tweets. The tweets were classified into either positive, neutral, or negative using the Valence Aware Dictionary or sEntiment Reasoner (VADER). Confusion matrix and classification reports bestow the precision, recall, and F1-score in identifying the best algorithm for classifying the sentiments.

• 한국문헌정보학회지
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• 제54권3호
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• pp.285-314
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• 2020

The healthcare environment is becoming increasingly dependent on health information technology (HIT), with healthcare providers, patients, and other people engaged in the field producing and sharing information to improve healthcare delivery. This focus has raised the issue of Health Information Infrastructure (HII) to the forefront of policy, design, and law. While several studies have examined each element of HII, little attention has been paid to the overall infrastructure as a collection of technologies, institutions, standards, and practices. In order to fill the gap, this study focuses on medication reconciliation as an example of the wider phenomenon of HII. In particular, the study examines a medication reconciliation process (MRP) as an example to understand the key challenges facing the development of HII, how the challenges are interrelated, and how they can be met as a whole. Following a mixed methodology, involving workflow study, focus group discussions, and in-depth interviews, the study examines "data friction" along technical, institutional, regulatory, and legal dimensions. This study constitutes one of the first efforts to comprehensively investigate health information infrastructure and how technology and other dimensions in infrastructure are interrelated. The study therefore contributes to a better understanding of HII and the practical challenges that hinder the seamless flow of information in the healthcare environment.

• 한국IT서비스학회지
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• 제10권3호
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• pp.77-94
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• 2011

Since the general quality of life has been improving, people have become interested in "well-being." The widespread acceptance of the importance of "well-being" to quality of life has encouraged people to take more interest in getting health information online when they need it. Expansive use of online health information suggests that individual characteristics (i.e., gender and other traits), Website features, and perceived trust are related to the primary concern for many online health information consumers. This study examines whether familiarity, perceived security, and reputation of health information on various Websites influence the relationship of trust and intention to use by gender. These research results will contribute to the adoption of online health information by gender and, moreover, will provide companies with an understanding of key characteristics of consumers who use emoticons and provide useful implications for marketing strategies to current and future consumers.

• 부모자녀건강학회지
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• 제3권1호
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• pp.27-34
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• 2000

In recent years, there has been a proliferation of consumer health information available on the internet related to parent-child health. More and more, parents are accessing information about child ca re through the Internet and computer at home. But there is no guarantee that the information is current, unbiased, or accurate. Several researchers have suggested some criteria for evaluating internet sites; source, accuracy, disclosure, currency, accessibility. As more consumer search the World Wide Web for parenting information, nurses have to learn more about this technology. Because nurses can assist parents in identifying how to locate information they can trust. It is also needed to for nurses to document the criteria for information selection on internet and to evaluate outcome of cyberspace intervention of parenting.