• Journal of Society of Preventive Korean Medicine
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• v.3 no.1
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• pp.67-82
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• 1999

This study was performed to investigate out-of-pocket money among medical expenses of an oriental medical university hospital by the use of internal data of an oriental hospital because medical insurance program data could not show us insuree's out-of-pocket money among medical expenses. The purpose of this study was to analyze out-of-pocket money among medical expenses of ambulatory and hospitalized patients. Under this purpose, We analyzed actual medical expenses data of 1389 out-patients and 858 in-patients of the oriental medical university hospital with 90 beds that could be approach to internal data from July 1, 1998 to March 31, 1999. The major findings are as follows : 1. In ambulatory patients, the cost share ratio of insuree & that of insurer was 90 : 10 respectly. 2. In hospitalized patients, the cost share ratio of insuree & that of insurer was 72 : 28 respectly.

• Korean Journal of Digital Imaging in Medicine
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• v.15 no.1
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• pp.9-20
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• 2013

PACS is one of the most used medical information system and share information from other hospitals through the PACS. Data integrity means zero defects data and this is a prerequisite of information system performance. but I wonder if I can trust these informations that Incorrect information from radiotechnologist's mistakes, anonymous in emergency department, Newborn baby department, modified informations at later. And Modified informations causes defect in integrity of the data. When we import, we use DICOM header not DB data. so error occurs that DB data is deferent with DICOM Header information. This paper discusses to resolve as above problem using DICOM object such as DICOM PR, SR. And propose quality management system that can guarantee the patient information and can manage exam history.

• Korean Medical Education Review
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• v.25 no.2
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• pp.84-101
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• 2023

Longitudinal data can provide important evidence with the potential to stimulate innovation and affect policies in medical education and can serve as a driving force for further developments in medical education through evidence-based decisions. Tracking and observing cohorts of students and graduates using longitudinal data can be a way to link the past, present, and future of medical education. This study reviewed practical methods and technical, administrative, and ethical considerations for the establishment and operation of a longitudinal database and presented examples of longitudinal databases. Cohort study design methods and previous examples of research using longitudinal databases to explore major topics in medical education were also reviewed. The implications of this study are as follows: (1) a systematic design process is required to establish longitudinal data, and each university should engage in ongoing deliberation about this issue; (2) efforts are needed to alleviate "survey fatigue" among respondents and reduce the administrative burden of those conducting data collection and analysis; (3) it is necessary to regularly review issues of personal information protection, data security, and ethics regarding the survey respondents; and (4) a system should be established that integrates and manages a longitudinal database of medical education at the national level. The hope is that establishing longitudinal data and cohorts at individual medical schools will not be a temporary phenomenon, but rather that they will be well utilized at the national level to innovate and implement ongoing changes in medical education.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.8
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• pp.2772-2786
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• 2022

We had researched an automatic authentication-supported medical information platform[6]. The proposed automatic authentication consists of user authentication and mobile terminal authentication, and the authentications are performed simultaneously in patients' emergency conditions. In this paper, we studied on finding emergency conditions for the automatic authentication by applying big data processing and AI mechanism on the extended medical information platform with an added edge computing system. We used big data processing, SVM, and 1-Dimension CNN of AI mechanism to find emergency conditions as authentication means considering patients' underlying diseases such as hypertension, diabetes mellitus, and arrhythmia. To quickly determine a patient's emergency conditions, we placed edge computing at the end of the platform. The medical information server derives patients' emergency conditions decision values using big data processing and AI mechanism and transmits the values to an edge node. If the edge node determines the patient emergency conditions, the edge node notifies the emergency conditions to the medical information server. The medical server transmits an emergency message to the patient's charge medical staff. The medical staff performs the automatic authentication using a mobile terminal. After the automatic authentication is completed, the medical staff can access the patient's upper medical information that was not seen in the normal condition.

• The Korean Journal of Emergency Medical Services
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• v.11 no.3
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• pp.111-118
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• 2007

Purpose : It was to present strategies on activation of prehospital medical direction in Korea. Methods : This study was conducted by analysing some papers on prehospital medical direction and statistical data from the National Emergency Management Agency. Results : There was no active application of medical direction methods such as Priority Dispatch System, Pre-Arrival Instructions, System Status Management and no data on prehospital medical direction. To estimate direct medical control on emergency patients who were sorted by EMTs in 2006 was only 2.5%. Conclusion : To improve prehospital medical direction, it needed to applicate data collecting & using system and in-direct & direct medical control by medical doctor.

• Journal of Electrical Engineering and Technology
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• v.10 no.6
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• pp.2384-2392
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• 2015

The technical development and practical applications of big-data for health is one hot topic under the banner of big-data. Big-data medical image fusion is one of key problems. A new fusion approach with coding based on Spherical Coordinate Domain (SCD) in Wireless Sensor Network (WSN) for big-data medical image is proposed in this paper. In this approach, the three high-frequency coefficients in wavelet domain of medical image are pre-processed. This pre-processing strategy can reduce the redundant ratio of big-data medical image. Firstly, the high-frequency coefficients are transformed to the spherical coordinate domain to reduce the correlation in the same scale. Then, a multi-scale model product (MSMP) is used to control the shrinkage function so as to make the small wavelet coefficients and some noise removed. The high-frequency parts in spherical coordinate domain are coded by improved SPIHT algorithm. Finally, based on the multi-scale edge of medical image, it can be fused and reconstructed. Experimental results indicate the novel approach is effective and very useful for transmission of big-data medical image(especially, in the wireless environment).

• Journal of Society of Preventive Korean Medicine
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• v.19 no.2
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• pp.51-56
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• 2015

Objective : We analyzed present condition of cooperative medical care using claims data of HEALTH INSURANCE REVIEW & ASSESSMENT SERVICE form patients treated by Korean-Western cooperative medicine. The study aimed to offer guidelines in selecting disease-related research in developing Korean-Western convergence technology. Method : Based on the patients using Korean medical service, we analyzed claims data of patients using Korean medical service and western medical service from January 2012 to December 2013. We were assigned to the server remotely. With the concept of 'episode of care', we rebuilt claims data and analyzed present condition of cooperative medical usage. Results : We analyzed present condition of cooperative medical care per episode of care. Among outpatients, Low back pain, lumbar region(M5456) was the highest number. Among inpatients, Sciatica due to intervertebral disc disorder(M511) was the highest number. Conclusion : Based on the claims data provided by HEALTH INSURANCE REVIEW & ASSESSMENT SERVICE, we have derived a list of multy frequently disease frequently treated by cooperative medical care by analyzing present condition.

• Journal of Biomedical Engineering Research
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• v.29 no.2
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• pp.164-171
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• 2008

Recently, many of hospitals have hurried to computerize the resulting data from medical devices, in order to introduce Electric Medical Record(EMR). In terms of the linkage between medical devices and hospital information systems, however, many difficulties have arisen due to some reasons such as the variety of prescription input, the format difference of the resulting data sheet, and the interface difference between medical devices from different companies. To solve these problems, many researches on standardization of the resulting data of medical devices have been performed. In this study, the linkage between hospital information systems and resulting datum in Electrocardiogram(ECG) generating biosignal waveform was tested by applying Medical waveform Format Encoding Rules(MFER) Version 1.02, which has more advantages than existing global standard. MFER viewer, in addition, was made to display the resulting data on a screen. The MFER viewer was tested and compared to the existing Scalable Vector Graphics (SVG) Viewer. The results showed that this method is more effective in the interface the data storage and application, because of simplicity and easiness in data applications. And the results show that the MFER is convenience and effective for physician. It is considered that the role of MFER as the interface in biosignal waveform including Electrocardiogram medical devices would expand in the near future.

• IE interfaces
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• v.17 no.4
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• pp.426-439
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• 2004

This research discusses knowledge contents needed to build an OLAP system for medical sector, OLAP functionalities from past studies, and a medical intelligence system which is a kind of OLAP. The knowledge requirements which consist of nine contents and OLAP fundamental functionalities are applied to the system. Most past studies have focused on developing a medical data warehouse rather than OLAP. The medical intelligence system supplies health care providers (i.e., doctors, clinicians, researchers and nurses) and non-providers (i.e., managers and business analysts) with multidimensional OLAP functionalities. The system can be used to gain a deeper understanding of specific medical issues. In this research, we focus not on medical data warehouse, but on the technical challenges of designing and implementing an effective medical intelligence system for health care information. An architecture is applied to developing the medical intelligence system for a medical center in order to illustrate its practical usage. Six packages in the developed system are discussed in this research: Explorer, Analyzer, Reporter, Statistician, Visualizer, and Meta Administrator packages. Evaluation of the system and ongoing research directions conclude the research.

• Journal of Institute of Convergence Technology
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• v.11 no.1
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• pp.1-5
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• 2021

Deep learning based methods achieve state-of-the-art accuracy, however, they typically rely on supervised training with large labeled datasets. It is known in many medical applications that labeling medical images requires significant expertise and much time, and typical hand-tuned approaches for data augmentation fail to capture the complex variations in such images. This paper proposes a 3D image augmentation method to overcome these difficulties. It allows us to enrich diversity of training data samples that is essential in medical image segmentation tasks, thus reducing the data overfitting problem caused by the fact the scale of medical image dataset is typically smaller. Our numerical experiments demonstrate that the proposed approach provides significant improvements over state-of-the-art methods for 3D medical image segmentation.