• The Journal of Bigdata
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• v.3 no.1
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• pp.73-82
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• 2018

At the core of future medicine is the realization of Precision Medicine centered on individuals. For this, we need to have an open ecosystem that can view, manage and distribute healthcare data anytime, anywhere. However, since healthcare data deals with sensitive personal information, a significant level of reliability and security are required at the same time. In order to solve this problem, the healthcare industry is paying attention to the blockchain technology. Unlike the existing information communication infrastructure, which stores and manages transaction information in a central server, the block chain technology is a distributed operating network in which a data is distributed and managed by all users participating in the network. In this study, we not only discuss the technical and legal aspects necessary for demonstration of healthcare data distribution using blockchain technology but also introduce KOREN SDI Network-based Healthcare Big Data Distribution Demonstration Study. In addition, we discuss policy strategies for activating blockchain technology in healthcare.

• The Journal of Bigdata
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• v.7 no.1
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• pp.29-36
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• 2022

The prevalence of stress and depression among emotional workers is increasing due to the rapid increase in emotional labor and service workers. However, the current mental health management of emotional workers is difficult to consider the emotional response at the time of stress situations, and the existing mental health management is limited because the individual's base state is not reflected. In this study, we present mental healthcare digital twin solution technology, a personalized stress risk management solution. For mental health risk management due to emotional labor, a solution simulation is performed to accurately predict stress risk through synchronization/modeling of dynamic objects in virtual space by extracting individual stress risk factors such as emotional/physical response and environment into various modalities. It provides a mental healthcare digital twin solution for predicting personalized mental health risks that can be configured with modalities and objects tailored to the environment of emotional workers and improved according to user feedback.

• The Journal of Bigdata
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• v.1 no.2
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• pp.79-89
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• 2016

News organizations are looking for a way that can be reused accumulated intellectual property in order to find a new insights. BBC is a worldwide media that continually enhances the value of the news articles by using Linked Data model. Thus, utilizing the Linked Data model, by reusing the stored articles, can significantly improve the value of news articles. In this paper, we conducted a study of Linked Data construction for the healthcare news from a newspaper company. The object names associated with medical description or connected to other published information have been constructed into Linked Open Data service. The results of the study are to systematically organize the news data that were accumulated rashly, and to provide the opportunity to find new insights that could not be found before by connecting to other published information. It may be able to contribute to reused news data. Finally, using SPARQL query language can contribute to interactively searched news data.

• 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.

• Journal of Digital Convergence
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• v.17 no.5
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• pp.145-155
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• 2019

The Healthcare supply chain management has recently attracted attention as a critical tool to improve service quality and reduce healthcare operational cost. Improving large hospital supply chain performance has become increasingly important as healthcare organizations strive to improve the service quality, while reducing the ever-increasing healthcare cost. This paper explores the strategic areas where the traditional supply chain management may enhance the overall performance of the large hospitals. Based on the literature review and relevant case analysis, this paper argues that the visibility, information sharing and standardization are the critical factors for deploying the supply chain principles, and also proposes the supply chain framework for efficient planning and execution, the use of RFID-enabled system for the end-to-end traceability of medical products, and cross-docking system for minimizing the inventory level in the hospital supply chain. Implications of the study findings are discussed.

• The Journal of the Convergence on Culture Technology
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• v.10 no.3
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• pp.391-396
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• 2024

This study proposes a novel reverse N-Gram approach to overcome the limitations of traditional N-Gram methods and enhance performance in building an entity dictionary specialized for the healthcare sector. The proposed reverse N-Gram technique allows for more precise analysis and processing of the complex linguistic features of healthcare-related big data. To verify the efficiency of the proposed method, big data on healthcare and digital health announced during the Consumer Electronics Show (CES) held each January was collected. Using the Python programming language, 2,185 news titles and summaries mentioned from January 1 to 31 in 2010 and from January 1 to 31 in 2024 were preprocessed with the new reverse N-Gram method. This resulted in the stable construction of a dictionary for natural language processing in the healthcare field.

• Journal of the Health Care and Life Science
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• v.11 no.1
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• pp.67-77
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• 2023

This paper aims as a prior study to cultivate artificial intelligence professionals at the level of colleges in the future by analyzing healthcare services and technologies using artificial intelligence technology. As artificial intelligence technology is recognized as a key engine or core technology in the future that will create national competitiveness and added value, advanced countries are investing a lot of attention and support in developing technologies as well as human resources at the national level. Korea is also promoting national-level R&D manpower training projects such as AI graduate program support projects, and investing heavily in fostering and securing its own artificial intelligence personnel, mainly by large companies, but there is a lack of artificial intelligence experts. This study analyzes the current status of healthcare services and technologies, industries, and artificial intelligence manpower training using artificial intelligence technology, and proposes directions for fostering artificial intelligence personnel at the level of colleges.

• Management & Information Systems Review
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• v.39 no.3
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• pp.17-35
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• 2020

The purpose of this study is to develop business models for current situational scenarios reflecting customer needs emphasize the need for implementing a logistics cooperation system by analyzing big data to strengthen SCM competitiveness capacities. For healthcare SCM competitiveness needed for the logistics cooperation usage intent, they were divided into product quality, price leadership, hand-over speed, and process flexibility for examination. The wordcloud results that analyzed major considerations to realize work efficiency between medical institutes, words like unexpected situations, information sharing, delivery, real-time, delivery, convenience, etc. were mentioned frequently. It can be analyzed as expressing the need to construct a system that can immediately respond to emergency situations on the weekends. Furthermore, in addition to pursuing communication and convenience, the importance of real-time information sharing that can share to the efficiency of inventory management were evident. Accordingly, it is judged that it is necessary to aim for a business model that can enhance visibility of the logistics pipeline in real-time using big data analysis on site. By analyzing the effects of the adaptability of a supply chain network for healthcare SCM competitiveness, it was revealed that obtaining competitive capacities is possible through the implementation of logistics cooperation. Stronger partnerships such as logistics cooperation will lead to SCM competitive capacities. It will be necessary to strengthen SCM competitiveness by searching for a strategic approach among companies in a direction that can promote mutual partnerships among companies using the joint logistics system of medical institutes. In particular, it will be necessary to search for ways to utilize HCSM through big data analysis according to the construction of a logistics cooperation system.

• The Korean Society of Law and Medicine
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• v.17 no.2
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• pp.315-346
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• 2016

With the development of big data processing technology, the potential value of healthcare big data has attracted much attention. In order to realize these potential values, various research using the healthcare big data are essential. However, the big data regulatory system centered on the Personal Information Protection Act does not take into account the aspect of big data as an economic material and causes many obstacles to utilize it as a research purpose. The regulatory system of healthcare information, centered on the primary purpose of patient treatment, should be improved in a way that is compatible with the development of technology and easy to use for public interest. To this end, it is necessary to examine the trends of overseas legal system reflecting the concerns about the balance of protection and utilization of personal information. Based on the implications of the overseas legal system, we can derive improvement points in the following directions from our legal system. First, a legal system that specializes in healthcare information and encompasses protection and utilization is needed. De-identification, which is an exception to the Privacy Act, should also clearly define its level. It is necessary to establish a legal basis for linking healthcare big data to create synergy effects in research. It is also necessary to examine the introduction of the opt-out system on the basis of the discussion on the foreign debate and social consensus. But most importantly, it is the people's trust in these systems.

• Proceedings of the Korea Contents Association Conference
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• 2017.05a
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• pp.31-32
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• 2017

데이터의 다양성은 빅데이터를 이용해 새로운 가치를 창출하는데 있어 매우 중요하다. 데이터의 다양성을 위해서 다양한 데이터의 연계는 필수적이며, 여러 활용영역 중에서도 보건의료분야에서의 데이터 연계는 그 요구가 특히 증가하고 있다. 또한 활용성에 있어서도 높은 기대전망이 있는 분야이다. 그러나 보건의료 데이터의 연계는 개인정보 중에서도 많은 민감 정보를 포함하고 있기 때문에, 이에 관한 개인정보 보호에 대한 이슈 해결이 선행되어야하며, 데이터 연계에 관련 있는 주체간의 합의 역시 선행되어야 한다.