• Korean Journal of Clinical Laboratory Science
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• v.54 no.1
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• pp.73-77
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• 2022

Blood products (BPs) can only be obtained through blood donation and hence represent a finite resource. BPs should therefore be used conservatively. However, BPs are being used indiscriminately without evidence. The purpose of this study was to evaluate the reasons for the use of BPs and their appropriateness. The investigation was carried out based on hemoglobin levels. Data were obtained from Nov 1, 2020, to Oct 31, 2021, from a hospital's OCS/EMR systems. The BPs were dispensed in 21,303 cases, and the number of hemoglobin levels >7.0 g/dL or higher among red blood cell drugs used by each treatment department was 1,173 (>7.0 g/dL). The misuse of blood transfusions is increasing social costs, with the adequacy of transfusion becoming increasingly important. Hence, each medical institution should review the transfusion guideline evaluation index, check the status of the release of BPs, and institute educational programs covering transfusion guidelines and continually evaluate their adequacy.

• Journal of the Korea Computer Graphics Society
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• v.29 no.3
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• pp.127-135
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• 2023

Accurate segmentation of histopathology whole slide images (WSIs) is a crucial task for disease diagnosis and treatment planning. However, conventional automated segmentation algorithms may not always be applicable to WSI segmentation due to their large size and variations in tissue appearance, staining, and imaging conditions. Recent advances in interactive segmentation, which combines human expertise with algorithms, have shown promise to improve efficiency and accuracy in WSI segmentation but also presented us with challenging issues. In this paper, we propose a novel interactive segmentation method, ZoomISEG, that leverages multi-resolution WSIs. We demonstrate the efficacy and performance of the proposed method via comparison with conventional single-scale methods and an ablation study. The results confirm that the proposed method can reduce human interaction while achieving accuracy comparable to that of the brute-force approach using the highest-resolution data.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.406-409
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• 2022

In recent years, the developments in technologies, such as AI systems, Blockchain, VR/AR, 3D printing, robotics, and nanotechnology, are reshaping the future of healthcare right before our eyes. And also, healthcare has seen a paradigm shift towards prevention-oriented medicine, with a focus on consumers requirements. The spread of infectious diseases such as Covid-19 have altered the definition of healthcare and treatment facilities, necessitating immediate action to redesign hospitals' physical environments, adapt communication models to address social distancing requirements, implement virtual health solutions, and establish new clinical protocols. Hospitals, which have traditionally served as the hub of healthcare systems, are pursuing or being forced to reestablish themselves against this landscape. Rather than only treating ailments, future healthcare is predicted to focus on wellness and prevention. In personalized care, long-term prevention strategies, remote monitoring, early diagnosis, and detection are critical. Given the growing interest in smart healthcare defined by these modern technologies, this study looked into the definitions and service kinds of smart healthcare. The background and technical aspects of smart hospitals were also explored through a literature review.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.5
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• pp.999-1008
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• 2023

Early prediction of chronic diseases such as diabetes is an important issue, and improving the accuracy of diabetes prediction is especially important. Various machine learning and deep learning-based methodologies are being introduced for diabetes prediction, but these technologies require large amounts of data for better performance than other methodologies, and the learning cost is high due to complex data models. In this study, we aim to verify the claim that DNN using the pima dataset and k-fold cross-validation reduces the efficiency of diabetes diagnosis models. Machine learning classification methods such as decision trees, SVM, random forests, logistic regression, KNN, and various ensemble techniques were used to determine which algorithm produces the best prediction results. After training and testing all classification models, the proposed system provided the best results on XGBoost classifier with ADASYN method, with accuracy of 81%, F1 coefficient of 0.81, and AUC of 0.84. Additionally, a domain adaptation method was implemented to demonstrate the versatility of the proposed system. An explainable AI approach using the LIME and SHAP frameworks was implemented to understand how the model predicts the final outcome.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.17 no.1
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• pp.38-46
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• 2024

In general, EEG signal analysis has been the subject of several studies due to its ability to provide an objective mode of recording brain stimulation, which is widely used in brain-computer interface research with applications in medical diagnosis and rehabilitation engineering. In this study, we developed EEG reception hardware to measure electroencephalograms and implemented a processing system, classifying it into server and data processing. It was conducted as an intermediate-stage research on the implementation of a brain-computer interface using electroencephalograms, and was implemented in the form of predicting the user's arm movements according to measured electroencephalogram data. Electroencephalogram measurements were performed using input from four electrodes through an analog-to-digital converter. After sending this to the server through a communication process, we designed and implemented a system flow in which the server classifies the electroencephalogram input using a convolutional neural network model and displays the results on the user terminal.

• Journal of Biomedical Engineering Research
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• v.45 no.3
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• pp.109-117
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• 2024

We developed a device that integrates digital otoscope and stethoscope for telemedicine. The integrated device was utilized for the collection of tympanic membrane images and cardiac auscultation data. Data accumulated on the platform server can support real-time diagnosis of heart and eardrum diseases using artificial intelligence. Public data from Kaggle were used for deep learning. After comparing with various deep learning models, the MobileNetV2 model showed superior performance in analyzing tympanic membrane data, and the VGG16 model excelled in analyzing cardiac data. The classification algorithm achieved an accuracy of 89.9% for eardrums data and 100% for heart sound data. These results demonstrate the possibility of diagnosing diseases without the limitations of time and space by using this platform.

• Journal of the Korean Society for Library and Information Science
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• v.58 no.3
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• pp.333-358
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• 2024

To promote libraries as "Libraries for All," it is essential to assess the current state of regional library infrastructures and explore policy support strategies for their improvement. This study develops the 'Library Vitality Index' as a metric to evaluate libraries' capabilities as sustainable infrastructures. The index assesses various aspects, including libraries' environmental responsiveness, accessible design, level of digital transformation, and capacity to provide universal cultural services. The research involved a comprehensive review of domestic and international cases, Delphi surveys, and expert group interviews to derive the final set of indicators. These indicators were weighted based on their importance using AHP analysis. The final index consists of three components: regional library activation (300 points), individual library capacity (470 points), and feedback systems (30 points), with a total of 800 points. The index includes 108 items, divided into 14 for regional library activation, 88 for individual library capacity, and 6 for feedback systems.

• The Korean Journal of Nuclear Medicine Technology
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• v.22 no.1
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• pp.23-27
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• 2018

Purpose The introduction of bone scan has been reported as a useful tool in the diagnosis, treatment, and treatment response of skeletal disease. The purpose of this study is to improve the anatomical information and tolerance of the bone by combining bone scan and pelvic X-ray without additional radiation exposure. Materials and Methods From November 2015 to August 2016, 236 patients(64 men and 172 women, average age $50.96{\pm}15.39years$) take Bone scan and Pelvis AP(Anteroposterior) X-ray scan at the National Cancer Center. The scan equipment was a gamma camera, Symbia Ecam (SIEMENS, Germany), and a digital x-ray, DRS-800 (Listem, Korea). Osirix version 3.8.1 (Osirix, USA) and Stata/SE version 14.0 (StataCorp, USA) were used for image combination and analysis. The patient was intravenously injected with $^{99m}Tc-DPD$ (740 MBq), and the scan was performed 2 to 4 hours later. Gamma camera image acquisition were Matrix size $256{\times}1024$, Zoom 1.00, and scan speed 17 cm/min. The digital X-ray was made with a collimator size of $14^{{\prime}{\prime}}{\times}17^{{\prime}{\prime}}$, 77 kVp (60 to 97 kVp) and an average of 30 mAs (20 to 48). ASIS and pubic symphysis Select virtual points then Combine three virtual points and pelvic contour lines. The acquired images were evaluated by three radiologists who worked for more than 5 years in the nuclear medicine department. Results Of the total 236 patients, 216 (91.53%) were matched. The median and range (min~max) of the age were 67 (46~81) years old in the unmatched group and 52 (22~87) years old in the matched group, The Wilcoxon rank-sum test was performed to determine whether age was different between the two groups. As a result, the age difference between the two groups was statistically significant at p < 0.0001. Of the 64 men, 60 (93.75%) were match and of the 172 women, 156 (93.75%) were match. There was no statistically significant difference according to gender(p = 0.4542). Of the 54 patients without pelvic lesions, 54 (100.00%) were match, and 162 (89.01%) of 182 patients with pelvic lesions were match. There was a statistically significant difference according to the presence of pelvic lesions. Conclusion There are many variables in the combination of bone scan and pelvic X-ray imaging, and the patient's age and pelvic lesion may have some effect on the image combination. This study is expected to be useful for the diagnosis of pelvic osteosarcoma of children without radiation exposure. It is expected that this combination of images will help to develop the nuclear medicine image.

• Progress in Medical Physics
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• v.23 no.1
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• pp.26-32
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• 2012

The magnification technique has recently become popular in bone radiography, mammography and other diagnostic examination. However, because of the finite size of X-ray focal spot, the magnification influences various imaging properties with resolution, noise and contrast. The purpose of study is to investigate the influence of magnification and focal spot size on digital imaging system using eDQE (effective detective quantum efficiency). Effective DQE is a metric reflecting overall system response including focal spot blur, magnification, scatter and grid response. The adult chest phantom employed in the Food and Drug Administration (FDA) was used to derive eDQE from eMTF (effective modulation transfer function), eNPS (effective noise power spectrum), scatter fraction and transmission fraction. According to results, spatial frequencies that eMTF is 10% with the magnification factor of 1.2, 1.4, 1.6, 1.8 and 2.0 are 2.76, 2.21, 1.78, 1.49 and 1.26 lp/mm respectively using small focal spot. The spatial frequencies that eMTF is 10% with the magnification factor of 1.2, 1.4, 1.6, 1.8 and 2.0 are 2.21, 1.66, 1.25, 0.93 and 0.73 lp/mm respectively using large focal spot. The eMTFs and eDQEs decreases with increasing magnification factor. Although there are no significant differences with focal spot size on eDQE (0), the eDQEs drops more sharply with large focal spot than small focal spot. The magnification imaging can enlarge the small size lesion and improve the contrast due to decrease of effective noise and scatter with air-gap effect. The enlargement of the image size can be helpful for visual detection of small image. However, focal spot blurring caused by finite size of focal spot shows more significant impact on spatial resolution than the improvement of other metrics resulted by magnification effect. Based on these results, appropriate magnification factor and focal spot size should be established to perform magnification imaging with digital radiography system.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.35 no.1
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• pp.68-82
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• 2017

Strengthening surveillance, one of the most important factors in the crime prevention environment of cultural heritages, has difficulty in evaluating and diagnosing the site. For this reasons, surveillance enhancement has been assessed by modelling the shape of cultural heritage, topography, and trees digitally. The purpose of this study is to develop the evaluation method of crime prevention environment for cultural heritage by using the 3D visual exposure index (3DVE) which can quantitatively evaluate the surveillance enhancement in three dimensions. For the study, the evaluation factors were divided into natural, organizational, mechanical, and integrated surveillance. To conduct the analysis, the buildings, terrain, walls, and trees of the study site were modeled in three dimensions and the analysis program was developed by using the Unity 3D. Considering the working area of the person, it is possible to analyze the surveillance point by dividing it into the head and the waist position. In order to verify the feasibility of the 3DVE as the analysis program, we assessed the crime prevention environment by digitally modeling the Donam Seowon(Historic Site No. 383) located in Nonsan. As a result of the study, it was possible to figure out the problems of patrol circulation, the blind spot, and the weak point in natural, mechanical, and organizational surveillance of Donam Seowon. The results of the 3DVE were displayed in 3D drawings, so that the position and object could be identified clearly. Surveillance during the daytime is higher in the order of natural, mechanical, and organizational surveillance, while surveillance during the night is higher in the order of organizational, mechanical, and natural surveillance. The more the position of the work area becomes low, the more it is easy to be shielded, so it is necessary to evaluate the waist position. It is possible to find out and display the blind spot by calculating the surveillance range according to the specification, installation location and height of CCTV. Organizational surveillance, which has been found to be complementary to mechanical surveillance, needs to be analyzed at the vulnerable time when crime might happen. Furthermore, it is note that the analysis of integrated surveillance can be effective in examining security light, CCTV, patrol circulation, and other factors. This study was able to diagnose the crime prevention environment by simulating the actual situation. Based on this study, consecutive researches should be conducted to evaluate and compare alternatives to design the crime prevention environment.