• Journal of Internet Computing and Services
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• v.23 no.3
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• pp.87-95
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• 2022

Recently, with the development of smart technology, in medical information platform, patient's biometric data is measured in real time and accumulated into database, and it is possible to determine the patient's emergency situations. Medical staff can easily access patient information after simple authentication using a mobile terminal. However, in accessing medical information using the mobile terminal, it is necessary to study authentication in consideration of the patient situations and mobile terminal. In this paper, we studied on medical information platforms based on big data processing and edge computing for supporting automatic authentication in emergency situations. The automatic authentication system that we had studied is an authentication system that simultaneously performs user authentication and mobile terminal authentication in emergency situations, and grants upper-level access rights to certified medical staff and mobile terminal. Big data processing and analysis techniques were applied to the proposed platform in order to determine emergency situations in consideration of patient conditions such as high blood pressure and diabetes. To quickly determine the patient's emergency situations, edge computing was placed in front of the medical information server so that the edge computing determine patient's situations instead of the medical information server. The medical information server derived emergency situation decision values using the input patient's information and accumulated biometric data, and transmit them to the edge computing to determine patient-customized emergency situation. In conclusion, the proposed medical information platform considers the patient's conditions and determine quick emergency situations through big data processing and edge computing, and enables rapid authentication in emergency situations through automatic authentication, and protects patient's information by granting access rights according to the patient situations and the role of the medical staff.

• Journal of Korean Medical classics
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• v.35 no.4
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• pp.1-9
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• 2022

Objectives : This study aims to increase efficiency of the prescription similarity analysis method that uses drug composition ratio. Methods : The controlled experiment compared result generation time, generated data quantity, and accuracy of results between previous and new analysis method on the 12,598 formulas and 61 prescription groups. Results : The control group took 346 seconds on average and generated 768,478 results, while the test group took 24 seconds and generated 241,739 results. The test group adopted a selective calculation method that only used overlapping data between two formulas instead of analyzing all number of cases. It simplified the data processing process, reducing the quantity of data that is required to be processed, leading to better system speed, as fast as 14.47 times more than previous analysis method with equal results. Conclusions : Efficiency for similarity analysis could be improved by reducing data span and simplifying the calculation processes.

• Journal of the Korean Society for Precision Engineering
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• v.26 no.12
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• pp.138-145
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• 2009

Custom medical treatment is being widely adapted to lots of medical applications. A technology for 3D modeling is strongly required to fabricate medical implants for individual patient. Needs on true 3D CAD data of a patient is strongly required for tissue engineering and human body simulations. Medical imaging devices show human inner section and 3D volume rendering images of human organs. CT or MRI is one of the popular imaging devices for that use. However, those image data is not sufficient to use for medical fabrication or simulation. This paper mainly deals how to generate 3D geometry data from those medical images. A new image processing technology is introduced to reconstruct 3D geometry of a human body vacancy from the medical images. Then a surface geometry data is reconstructed by using Marching cube algorithm. Resulting CAD data is a custom 3D geometry data of human vacancy. This paper introduces a novel 3D reconstruction process and shows some typical examples with implemented software.

• Journal of the Korea Society of Computer and Information
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• v.7 no.4
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• pp.8-15
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• 2002

This Paper proposes designing and implementing the database system storing the medical images. This system collects the medical image when doctors operate and diagnose the patients using the endoscope in the orthopedics, then stores the medical image data to database. Therefore. system avoids duplicated medical data, retrieves and updates the medical data effectively. The medical image data can be shared to the multiple users and application programs. This system consists of the five components. that is, the input module acquiring the medical image from the endoscope. the modulo storing the medical image. the database design and implementation storms the patient's disease history and the medical image data, user friendly interface design and implementation, and the simple data retrieval engine. The features of the system are followed. The image catcher program using DirectShow is portable any image catcher board And because the image catcher algorithm is implemented as a public module, The throughput can be increased during the development of video and audio contents on internet.

• The Transactions of the Korea Information Processing Society
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• v.5 no.12
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• pp.3275-3284
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• 1998

In this paper, we deseribe a Medical Image Information System. Our system stores and manages 5 dimensional medical image data and provides the 3 dimensional medical data via the Internet. The Internet standard VR format. VRML(Virtual Reality Modeling Language) is used to represent the 3I) medical image data. The 3D images are reconstructed from medical image data which are enerated by medical imaging systems such ans CT(Computerized Tomography). MRI(Magnetic Resonance Imaging). PET(Positron Emission Tomograph), SPECT(Single Photon Emission Compated Tomography). We implemented the medical image information system shich rses a surface-based rendering method for the econstruction of 3D images from 2D medical image data. In order to reduce the size of image files to be transfered via the Internet. The system can reduce more than 50% for the triangles which represent the surfaces of the generated 3D medical images. When we compress the 3D image file, the size of the file can be redued more than 80%. The users can promptly retrieve 3D medical image data through the Internet and view the 3D medical images without a graphical acceleration card, because the images are represented in VRML. The image data are generated by various types of medical imaging systems such as CT, MRI, PET, and SPECT. Our system can display those different types of medical images in the 2D and the 3D formats. The patient information and the diagnostic information are also provided by the system. The system can be used to implement the "Tele medicaine" systems.

• Journal of Information Processing Systems
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• v.12 no.1
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• pp.129-148
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• 2016

Acute myocardial infarction (AMI) is one of the three emergency diseases that require urgent diagnosis and treatment in the golden hour. It is important to identify the status of the coronary artery in AMI due to the nature of disease. Therefore, multi-modal medical images, which can effectively show the status of the coronary artery, have been widely used to diagnose AMI. However, the legacy system has provided multi-modal medical images with flat and unstructured data. It has a lack of semantic information between multi-modal images, which are distributed and stored individually. If we can see the status of the coronary artery all at once by integrating the core information extracted from multi-modal medical images, the time for diagnosis and treatment will be reduced. In this paper, we analyze semantic relations between multi-modal medical images based on coronary anatomy for AMI. First, we selected a coronary arteriogram, coronary angiography, and echocardiography as the representative medical images for AMI and extracted semantic features from them, respectively. We then analyzed the semantic relations between them and defined the convergence data model for AMI. As a result, we show that the data model can present core information from multi-modal medical images and enable to diagnose through the united view of AMI intuitively.

• Journal of Korean Academy of Nursing Administration
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• v.14 no.4
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• pp.396-403
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• 2008

Purpose: The purpose of this study was to identify experiences when Koreans who reside in Thailand visit Thai health facilities. Methods: The data were collected via direct interview from 36 Korean residents of Thailand. Collected data were analyzed by content analysis. Result: 1) 162 content analysis data were collected from the participants' statements. These data were categorized into 70 attributes and 9 higher attributes. 2) Out of the 70 attributes, the 3 attributes which were most commonly mentioned by the participants were the following: medical expense for foreigners were expensive(66.7%), difficulties in communication with health care providers(36.1%), kindness of nurses(33.3%). 3) The 9 higher attributes were 1) high medical expense to foreigner, 2) difficulties in communication, 3) distrust about medical service, 4) excessive prescription in oral medicine, 5) kindness, 6) good service, 7) difference in medical environment according hospital type, 8) irrational process in medical treatment for out patients, 9) cultural difference in postpartum care. Conclusion: When Korean residents in Thailand use Thailand health facilities, they experience high medical expense, difficulties in communication, low quality in medical service and kindness of the medical staff.

• Journal of Convergence for Information Technology
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• v.9 no.9
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• pp.195-200
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• 2019

The purpose of this study is to analyze the characteristics of National Health Insurance claim data and to construct a pilot medical episode data considering it. In this study, the trends of respiratory disease (ICD10: J00-J99) cardiovascular disease (ICD10: I00-I99) from the day of onset of treatment to re-admission after admission were confirmed in Seoul, and the largest decrease was observed when the no-treatment period was 0 day. The data reduction rate when the no-treatment period is 0 day is judged to be due to the monthly separation claim of the health insurance claim data. Also, the result that there is a tendency of monthly separation request according to the type of medical treatment. Through this study, we constructed epidemic data for the pilot medical treatment considering the characteristics of the claim data of health insurance, and based on this, it can be used as a data processing method for calculating basic epidemiological information.

• Journal of The Korea Institute of Healthcare Architecture
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• v.6 no.10
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• pp.23-30
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• 2000

The purpose of this study is to provide the basic data that helps the supplying medical resources through understanding the present conditions of medical resources and the territory of diagnosis in Uijongbu city. To achieve this goal, the statistical data related to the medical resources of Uijongbu city were analyzed; the number of population, medical facility, beds for inpatients, medical personnels and so on. Through the analysis of statistical data, it was revealed that the present conditions of medical resources are so insufficient in Uijongbu city. The results of the study were as follows; Firstly, it should be added to the beds for inpatients. Secondly, it should be characterized by specialization of hospitals. Thirdly, it should be added to the herb medicine hospital.

• International Journal of Computer Science & Network Security
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• v.24 no.1
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• pp.9-16
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• 2024

AI or Artificial Intelligence has been a significant tool used in the organisational backgrounds for an effective improvement in the management methods. The processing of the information and the analysis of the data for the further achievement of heightened efficiency can be performed by AI through its data analytics measures. In the medical field, AI has been integrated for an improvement within the management of the medical services and to note a rise in the levels of customer satisfaction. With the benefits of reasoning and problem solving, AI has been able to initiate a range of benefits for both the consumers and the medical personnel. The main benefits which have been noted in the integration of AI would be integrated into the study. The issues which are noted with the integrated AI usage for the medical sector would also be identified in the study. Medical Image Processing has been seen to integrate 3D image datasets with the medical industry, in terms of Computed Tomography (CT) or Magnetic Resonance Imaging (MRI). The usage of such medical devices have occurred in the diagnosis of the patients, the development of guidance towards medical intervention and an overall increase in the medical efficiency. The study would focus on such different tools, adhered with AI for increased medical improvement.