• The Korean Journal of Emergency Medical Services
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• v.19 no.2
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• pp.83-97
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• 2015

Purpose: Although appointed as a national competency standards (NCS) based reserves department, the department of emergency medical technology, an NCS-based emergency department, is mainly focused on subject deduction for a NCS-based curriculum. Methods: Job models were formed and verified by combining the competency unit of NCS and the duty of Developing a curriculum (DACUM) based on the development procedure indicated in the guidelines for a NCS-based curriculum. The mapping method of the subject was performed by deducting necessary competency units (duty) and competency unit elements (task) by connecting with the composition items of NCS and DACUM. Results: Job models combined with job analysis for the NCS and DACUM were reduced to 13 competency units (duty) and 79 competency unit elements (task). A modified method such as the 1:N method was mainly applied as a subject-matching method with consideration of the competency level and size of the competency unit. Conclusion: It would be a desirable direction to develop a NCS-based curriculum in the center of the practice subject in consideration of the size of the competency unit and competency level of the competency unit element. The existing curriculum should be promoted as a field-oriented curriculum at the complementary level.

• BMB Reports
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• v.43 no.5
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• pp.375-381
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• 2010

In this study, the cDNA library of Chang-liver cells was immunoscreened using common ADAMs antibody to obtain ADAM related genes. We found one positive clone that was confirmed as a new gene by Blast, which is an uncharacterized helical and coil protein and processes protease activity, and named protease-related protein 1 (ARP1). The submitted GenBank accession number is AY078070. Molecular characterizations of ARP1 were analyzed with appropriate bioinformatics software. To analyse its expression and function, ARP1 was subcloned into glutathione S-transferase fusion plasmid pGEX-2T and expressed by E. coli system. The in vitro expression product of ARP1 was recognized by common ADAMs antibody with western blot. Interestingly, ARP1 cleaves gelatine at pH9.5, which suggests it is an alkaline protease. Semi-quantitative RT-PCR result indicates that ARP1 mRNA is strongly transcribed in the liver and the treated Chang-liver cells.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.6B
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• pp.962-969
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• 2010

Recently, RFID technology can successfully be used to reduce medical errors. This technology can aid in the accurate matching of patients with their medications and treatments. The enthusiasm for using RFID technology in medical settings has been tempered by privacy concerns. In this paper, we propose a secure and efficient RFID authentication system to not only authenticate patients' authenticity but also protect patients' personal medical informations. The proposed system consists of RFID-based patient authentication protocol and database security protocol. As a result, since the proposed RFID authentication system provides strong security and efficiency, it can be used practically for patient authentication and personal medical information protection on the high technology medical environments such as u-Hospital and u-Healthcare.

• Progress in Medical Physics
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• v.31 no.3
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• pp.124-134
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• 2020

Here we review the evolutionary history of radiation therapy technology through the festschrift of articles in celebration of the 30th anniversary of Korean Society of Medical Physics (KSMP). Radiation therapy technology used in clinical practice has evolved over a long period of time. Various areas of science, such as medical physics, mechanical engineering, and computer engineering, have contributed to the continual development of new devices and techniques. The scope of this review was restricted to two areas; i.e., output energy production and functional development, because it is not possible to include all development processes of this technology due to space limitations. The former includes the technological transition process from the initial technique applied to the first model to the latest technique currently used in a variety of machines. The latter has had a direct effect on treatment outcomes and safety, which changed the paradigm of radiation therapy, leading to new guidelines on dose prescriptions, innovation of dose verification tools, new measurement methods and calculation systems for radiation doses, changes in the criteria for errors, and medical law changes in all countries. Various complex developments are covered in this review. To the best of our knowledge, there have been few reviews on this topic and we consider it very meaningful to provide a review in the festschrift in celebration of the 30th anniversary of the KSMP.

• International Journal of Advanced Culture Technology
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• v.11 no.1
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• pp.283-289
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• 2023

AI is bringing about drastic changes not only in the aspect of technologies but also in society and culture. Medical AI based on deep learning have developed rapidly. Especially, the field of medical image analysis has been proven that AI can identify the characteristics of medical images more accurately and quickly than clinicians. Evaluating the latest results of the AI-based medical image processing is important for the implication for the development direction of medical AI. In this paper, we analyze and evaluate the latest trends in AI-based medical image analysis, which is showing great achievements in the field of medical AI in the healthcare industry. We analyze deep learning models for medical image analysis and AI-based medical image segmentation for quantitative analysis. Also, we evaluate the future development direction in terms of marketability as well as the size and characteristics of the medical AI market and the restrictions to market growth. For evaluating the latest trend in the deep learning-based medical image processing, we analyze the latest research results on the deep learning-based medical image processing and data of medical AI market. The analyzed trends provide the overall views and implication for the developing deep learning in the medical fields.

• Journal of Internet Computing and Services
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• v.18 no.6
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• pp.75-84
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• 2017

As there has been growing interests in PHR-based personalized health management project, various institutions recently explore safe methods of recording personal medical and health information. In particular, innovative medical solution can be realized when medical researchers and medical service institutes can generally get access to patient data. As EMR data is extremely sensitive, there has been no progress in clinical information exchange. Moreover, patients cannot get access to their own health data and exchange it with researchers or service institutions. It can be operated in terms of technology, yet policy environment are affected by state laws as well as Privacy and Security Policy. Blockchain technology-independent, in transaction, and under test-is introduced in the medical industry in order to settle these problems. In other words, medical organizations can grant preliminary approval on patient information exchange by using the safely encrypted and distributed Blockchain ledger and can be managed independently and completely by individuals. More apparently, medical researchers can gain access to information, thereby contributing to the scientific advance in rare diseases or minor groups in the world. In this paper, we focused on how to manage personal medical information and its protective use and proposes medical treatment exchange system for patients based on a permissioned Blockchain network for the safe PHR operation. Trusted Model for Sharing Medical Data (TMSMD), that is proposed model, is based on exchanging information as patients rely on hospitals as well as among hospitals. And introduce medical treatment exchange system for patients based on a permissioned Blockchain network. This system is a model that encrypts and records patients' medical information by using this permissioned Blockchain and further enhances the security due to its restricted counterfeit. This provides service to share medical information uploaded on the permissioned Blockchain to approved users through role-based access control. In addition, this paper presents methods with smart contracts if medical institutions request patient information complying with domestic laws by using the distributed Blockchain ledger and eventually granting preliminary approval for sharing information. This service will provide an independent information transaction and the Blockchain technology under test will be adopted in the medical industry.

• Korean Medical Education Review
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• v.22 no.2
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• pp.99-114
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• 2020

The rapid development of artificial intelligence (AI), including deep learning, has led to the development of technologies that may assist in the diagnosis and treatment of diseases, prediction of disease risk and prognosis, health index monitoring, drug development, and healthcare management and administration. However, in order for AI technology to improve the quality of medical care, technical problems and the efficacy of algorithms should be evaluated in real clinical environments rather than the environment in which algorithms are developed. Further consideration should be given to whether these models can improve the quality of medical care and clinical outcomes of patients. In addition, the development of regulatory systems to secure the safety of AI medical technology, the ethical and legal issues related to the proliferation of AI technology, and the impacts on the relationship with patients also need to be addressed. Systematic training of healthcare personnel is needed to enable adaption to the rapid changes in the healthcare environment. An overall review and revision of undergraduate medical curriculum is required to enable extraction of significant information from rapidly expanding medical information, data science literacy, empathy/compassion for patients, and communication among various healthcare providers. Specialized postgraduate AI education programs for each medical specialty are needed to develop proper utilization of AI models in clinical practice.

• Journal of radiological science and technology
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• v.8 no.2
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• pp.89-91
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• 1985

• Journal of radiological science and technology
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• v.9 no.1
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• pp.83-87
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• 1986

• Journal of radiological science and technology
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• v.3 no.1
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• pp.114-123
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• 1980