• The Korean Journal of Emergency Medical Services
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• v.6 no.1
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• pp.27-37
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• 2002

The health and medical service attracts more public attention as the economy of Korea is rapidly growing up and the standard of living is elevated. Especially, the interest and demand on the prehospital emergency medical service that consists of the important part of primary medical service that is directly related to the life of patients are gradually increased. However, as compared with other advanced countries such as America in this area, Korea actually fell behind in the utilization of IT (Information Technology) to maximize the efficiency of emergency service system as well as has a problem in the general service system. This study suggested the necessity to introduce EMD (Emergency Medical Dispatch) system that takes a great role as the core part in the prehospital emergency medical service that is not systemized in Korea yet. In addition, this study proposed the implementation model of EMD ASP system using ASP (Application Service Provider) in EMD system to flexibly deal with the change of IT and efficient implementation and integration of information system as well as to significantly reduce cost through wire/wireless high speed Internet network that is politically promoted in Korea on the basis of EMD. The system analysis and design was executed by HIPO (Hierarchy Plus Input Process Output) analysis that was the conceptual design technology for EMD information system modeling based on ASP and DFD (Data Flow Diagram). This study proposed DB table configuration and data schema to implement the application of web browser interface in EMD system through ERD(ER-Diagram) of EMD ASP system. Finally, this study described how to implement and utilize EMD information system. This study aims to facilitate the qualitative development of emergency medical service in the future as suggesting the concrete models for the implementation of high value-added prehospital emergency medical information system as applying ASP concept to EMD system of prehospital emergency medical service area.

• Analytical Science and Technology
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• v.37 no.5
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• pp.261-270
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• 2024

This study examines portable Gas Chromatography (GC) for the quantitative analysis of oxygen and impurities, focusing on the development and validation of a method to determine oxygen, carbon monoxide, carbon dioxide, methane, and nitrogen in medical compressed oxygen gas. The goal is to ensure the quality of medicalgrade oxygen. The method's validation assessed its metrological characteristics, demonstrating specificity through clear chromatographic separation of the target gases and the absence of these peaks in the carrier gas chromatogram. It exhibited linearity within the designated concentration ranges, while precision met permissible standards, with the relative standard deviation for intermediate precision being less than 4% for carbon monoxide (0.00025 - 0.00099 %), less than 3 % for methane (0.0005 - 0.00246%) and carbon dioxide (0.0050 - 0.0150 %), less than 2% for nitrogen (0.1 - 0.7 %), and less than 0.01% for oxygen (99.27 - 99.98%). Overall, the validation results confirm the suitability of this analytical method for the quantitative determination of the aforementioned gases in medical compressed oxygen using portable GC with microchromatographic columns and detectors.

• The Journal of the Korea Contents Association
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• v.14 no.5
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• pp.1-7
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• 2014

Nowadays hospitals have been improving their job performances through informatization and also establishing an advanced, integrated medical information system through their manager's decision making support system in order to play roles as a hub hospital providing high quality medical services integrated with ICT technology. This study connects the OCS system and HIS system to the integrated medical information system to design an optimized, customized mobile health care and medical treatment environment and also investigates the systematic medical system that can perform patients' cure and medical treatment promptly and accurately in order to maximize convenience of treatment by inquiring into patients' information and information of medical treatment promptly.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.9
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• pp.317-322
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• 2022

The rapid development of information technology is also bringing about many changes in the medical environment. In particular, it is leading the rapid change of medical image information systems using big data and artificial intelligence (AI). The prescription delivery system (OCS), which consists of an electronic medical record (EMR) and a medical image storage and transmission system (PACS), has rapidly changed the medical environment from analog to digital. When combined with multiple solutions, PACS represents a new direction for advancement in security, interoperability, efficiency and automation. Among them, the combination with artificial intelligence (AI) using big data that can improve the quality of images is actively progressing. In particular, AI PACS, a system that can assist in reading medical images using deep learning technology, was developed in cooperation with universities and industries and is being used in hospitals. As such, in line with the rapid changes in the medical image information system in the medical environment, structural changes in the medical market and changes in medical policies to cope with them are also necessary. On the other hand, medical image information is based on a digital medical image transmission device (DICOM) format method, and is divided into a tomographic volume image, a volume image, and a cross-sectional image, a two-dimensional image, according to a generation method. In addition, recently, many medical institutions are rushing to introduce the next-generation integrated medical information system by promoting smart hospital services. The next-generation integrated medical information system is built as a solution that integrates EMR, electronic consent, big data, AI, precision medicine, and interworking with external institutions. It aims to realize research. Korea's medical image information system is at a world-class level thanks to advanced IT technology and government policies. In particular, the PACS solution is the only field exporting medical information technology to the world. In this study, along with the analysis of the medical image information system using big data, the current trend was grasped based on the historical background of the introduction of the medical image information system in Korea, and the future development direction was predicted. In the future, based on DICOM big data accumulated over 20 years, we plan to conduct research that can increase the image read rate by using AI and deep learning algorithms.

• Industry Promotion Research
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• v.7 no.3
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• pp.17-26
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• 2022

As the well-being mindset to keep our minds and bodies free and healthy more than anything else in the society we live in is spreading, the meaning of health care has become a key part of the 4th industrial revolution such as big data, IoT, AI, and block chain. The advancement of the advanced medical information service industry is being promoted by utilizing convergence technology. In digital healthcare, the development of intelligent information technology such as artificial intelligence, big data, and cloud is being promoted as a digital transformation of the traditional medical and healthcare industry. In addition, due to rapid development in the convergence of science and technology environment, various issues such as health, medical care, welfare, etc., have been gradually expanded due to social change. Therefore, in this study, first, the general meaning and current status of digital health care medical information is examined, and then, developmental tasks to activate digital health care medical information are analyzed and reviewed. The purpose of this article is to improve usability to fully pursue our human freedom.

• Journal of Electrical Engineering and Technology
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• v.11 no.2
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• pp.499-507
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• 2016

Medical imaging techniques such as Magnetic Resonance Imaging (MRI), Computed Tomography (CT) and Ultrasound (US) produce a large amount of digital medical images. Hence, compression of digital images becomes essential and is very much desired in medical applications to solve both storage and transmission problems. But at the same time, an efficient image compression scheme that reduces the size of medical images without sacrificing diagnostic information is required. This paper proposes a novel threshold-based medical image compression algorithm to reduce the size of the medical image without degradation in the diagnostic information. This algorithm discusses a novel type of thresholding to maximize Compression Ratio (CR) without sacrificing diagnostic information. The compression algorithm is designed to get image with high optimum compression efficiency and also with high fidelity, especially for Peak Signal to Noise Ratio (PSNR) greater than or equal to 36 dB. This value of PSNR is chosen because it has been suggested by previous researchers that medical images, if have PSNR from 30 dB to 50 dB, will retain diagnostic information. The compression algorithm utilizes one-level wavelet decomposition with threshold-based coefficient selection.

• Journal of Korea Society of Industrial Information Systems
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• v.18 no.3
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• pp.47-56
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• 2013

With the development of the morden medical science technology, the life of the men is keeping by medical technology. But if a proper treatment could not be provided to the patient in pre-hospital phase and the patient could not be transferred to the necessary hospital timely, it can not prevent the serious damage to the patient. In this paper, when an emergency was generated, the emergency medical technician can give the most suitable first aid to the patient by our proposed efficient emergency medical information system using heuristic knowledge.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.78-79
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• 2018

Recently, medical technology and IT technology have been trying to converge to overcome limitations of the time and the space in medical technology application. In this study, an app was developed to support remote medical direction for emergency medical services. The developed app allows doctors in remote locations to receive real-time emergency patient situations from emergency paramedics. It can also guide the patient's condition diagnosis and emergency treatment and enable rapid response from the emergency room.

• Journal of Korea Society of Industrial Information Systems
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• v.15 no.2
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• pp.115-126
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• 2010

Modern society can be described as ubiquitous computing over the concept of information. Information technology(IT) has been developing in a way that relative technologies are integrated to each other. Especially in ubiquitous environment, medical information industry shows significant interest in the U-healthcare service area. This paper will first look into U-healthcare service environment and component of Integrated Medical Information Systems(IMIS). Secondly, it examines the basic technological factors for integrated medical information systems, which is datawarehouse, network, communication standards and technology related U-healthcare service. Finally it proposes how to implement and operate new integrated medical information system for ubiquitous health care service. The system will do point of care(POC) for customers by real time and diagnose them using their various and personal medical data. The information will be communicated back to the customers, which will improve their satisfaction.

• 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.