• Journal of the Korean Society of Radiology
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• v.15 no.3
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• pp.301-306
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• 2021

The use of tin filters as a way to reduce the medical radiation in computed tomography (CT). However, due to the changed X-ray spectrum with the use of tin filters, disease diagnosis could be affected because it appears as images of different impressions from previous images. Therefore, this study evaluates the changes in images when using tin filter and high pitch in chest low-dose CT. In this study, images were acquired in groups of three for comparison. Group 1 did not apply to tin filter, and used the existing pitch 0.8. Group 2 used a tin filter, pitch 0.8, Group 3 used a tin filter, and pitch 2.5. To compare the image quality, the natural image quality evaluator (NIQE) and the blind/referenceless image quality evaluator (BRISQUE) were used among the blind quality evaluation factors depended on a no-reference basis. As a result, the NIQE values were low in the order of Group 1, Group 3, and Group 2. BRISQUE values were low in the order of Group 3, Group 2 and Group 1. This study confirms the superiority of images of tin filter and high pitch techniques in chest low-dose CT, which is considered to be a fundamental study for acquiring accurate images of patients with difficult breathing control.

• The Journal of the Acoustical Society of Korea
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• v.41 no.5
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• pp.507-517
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• 2022

The PhotoAcoustic Microscopy (PAM) has been proved to be a useful tool for biological and medical applications due to its high spatial and contrast resolution. PAM is based on transmission of laser pulses and reception of PA signals. Since the strength of PA signals is generally low, not only are high-performance optical and acoustic modules required, but high-performance electronics for imaging are also particularly needed for high-quality PAM imaging. Most PAM systems are implemented with a combination of several pieces of equipment commercially available to receive, amplify, enhance, and digitize PA signals. To this end, PAM systems are inevitably bulky and not optimal because general purpose equipment is used. This paper reports a PA signal receiving system recently developed to attain the capability of improved Signal to Noise Ratio (SNR) and Contrast to Noise Ratio (CNR) of PAM images; the main module of this system is a low noise, wideband signal receiver that consists of two low-noise amplifiers, two variable gain amplifiers, analog filters, an Analog to Digital Converter (ADC), and control logic. From phantom imaging experiments, it was found that the developed system can improve SNR by 6.7 dB and CNR by 3 dB, compared to a combination of several pieces of commercially available equipment.

• The Journal of Bigdata
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• v.8 no.2
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• pp.125-131
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• 2023

Globally, drug side effects rank among the top causes of death. To effectively respond to these adverse drug reactions, a shift towards an active real-time monitoring system, along with the standardization and quality improvement of data, is necessary. Integrating individual institutional data and utilizing large-scale data to enhance the accuracy of drug side effect predictions is critical. However, data sharing between institutions poses privacy concerns and involves varying data standards. To address this issue, our research adopts a federated learning approach, where data is not shared directly in compliance with privacy regulations, but rather the results of the model's learning are shared. We employ the Common Data Model (CDM) to standardize different data formats, ensuring accuracy and consistency of data. Additionally, we propose a drug monitoring system that enhances security and scalability management through a cloud-based federated learning environment. This system allows for effective monitoring and prediction of drug side effects while protecting the privacy of data shared between hospitals. The goal is to reduce mortality due to drug side effects and cut medical costs, exploring various technical approaches and methodologies to achieve this.

• Korea Journal of Hospital Management
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• v.14 no.4
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• pp.25-51
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• 2009

This model was empirically developed to test the effect of medical service quality and hospital's reputation on customer satisfaction, repurchase intention, and negative word of mouth as to disease severity. The model was tested in the context of the hospital industry. The findings are as follows. First, medical service provider's functional quality and technical service quality have significant effect on customer satisfaction. Second, hospital's reputation has positive(+) effect on customer satisfaction and significant negative effect on negative word of mouth. Third, customer satisfaction with medical service quality has significantly positive effect on customer's repurchase intention and has negative(-) effect on customer's negative word of mouth. Furthermore, customer's negative word of mouth has negative effect on their repurchase intention. Fourth, as to different disease severity, medical service quality and hospital's reputation have different effect on customer satisfaction, repurchase intention, and negative word of mouth. When patients get slightly ill, functional service quality and technical service quality have direct influence on customer satisfaction which has positive influence on repurchase intention and negative influence on negative word of mouth. Finally, negative word of mouth has negative effect on customer's repurchase intention. However, while hospital's reputation doesn't have effect on customer satisfaction, the reputation has significantly negative effect on negative word of mouth. When patients get seriously ill, only functional service quality has positive effect on customer satisfaction which influences on customer's repurchase intention and negatively influences on negative word of mouth. On the contrary, negative word of mouth doesn't influence on customer's repurchase intention as patients want to treat serious diseases in the large general hospitals even though negative word of mouth is known to them.

• Journal of the Korean Society of Radiology
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• v.12 no.5
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• pp.575-582
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• 2018

This article compared accuracy of 5 types of radionuclide activity meters that are being used in medical institutions and proposed the correction factor for each radionuclide activity meters type, using Ge-68/Ga-68 radiation sources for scanner setting, regular scanner correction, attenuation correction, and normalization. The calibration constant between baseline values and measured values by CRC-15R, CRC-15 PET, CRC-712M, CRC-15 Beta, and CRC-25PET was 0.99999(P<0.0001), which showed very high linearity. In the accuracy test, CRC-15R, CRC-15 PET, CRC-712M, CRC-15 Beta, and CRC-25PET model showed -3.232%, -1.342%, -2.815%, -2.913%, and -3.089% respectively.

• The Journal of the Acoustical Society of Korea
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• v.34 no.3
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• pp.210-218
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• 2015

When the driving voltage of an ultrasound transducer is increased to improve the quality of ultrasound images, heat is generated inside the transducer that can cause patient's skin burn and degradation of transducer performance. Hence, in this paper, a method to disperse the heat of the transducer has been studied. The phased array transducer having 3 MHz center frequency and 32 channels was selected for analyses of the thermal dispersion. First, mechanism of the heat generation was investigated in relation to the transducer operation through theoretical analysis, and material damping and sound pressure amplitude were confirmed to be influential on the heat generation. Further, we investigated the effects of the properties of the materials constituting the transducer on the thermal dispersion through finite element analysis. Based on the analysis results, we determined the thermal properties of the constituent materials that could facilitate the thermal dispersion inside the transducer. The determined thermal properties were applied to the finite element model, and the results showed that the maximum temperature at an acoustic lens contacting with a patient was decreased to 51 % of its initial value.

• Journal of KIISE
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• v.43 no.9
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• pp.953-962
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• 2016

Model-based testing is a technique for performing the test by using a model that represents the behavior of the system as a system specification. Industrial domains such as automotive, military/aerospace, medical, railway and nuclear power generation require model-based testing and code coverage-based testing to improve the quality of software. Despite the fact that both model-based testing and code coverage-based testing are required, difficulty in achieving a high coverage using model-based testing caused by the abstraction level difference between the test model and the source code, results in the need for performing model-based testing separately. In this study, to overcome the limitations of the existing model-based testing, we proposed the state machine transformation method to effectively improve the code coverage using the protocol state machine, one of the typical modeling methods is used as the test model in model-based testing, as the test model. In addition, we performed a case study of both systems and analyzed the effectiveness of the proposed method.

• Journal of Information Technology and Architecture
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• v.11 no.1
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• pp.45-52
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• 2014

Recently, more and more hospitals have become interested in the innovation of healthcare services and processes through IT convergence based on RFID, NFC, smart devices and so on. This paper presents a case of process innovation by implementing a smart health checkup system using these advanced information technologies. The existing inefficient health checkup process based on the paper chart and manual work has been innovated using the advanced information and communication technologies. The newly developed smart health checkup system has been used successfully in a tertiary university hospital named Samsung Medical Center since April 2013. The contributions of the system include improvement of service quality, enhancement of customer satisfaction, reduction in workload of staffs, improvement of work accuracy, and accordingly reinforcement of the competitiveness of the hospital.

• Journal of radiological science and technology
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• v.32 no.1
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• pp.17-24
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• 2009

Noise evaluation for an image has been performed by root mean square (RMS) granularity, autocorrelation function (ACF), and Wiener spectrum. RMS granularity stands for standard deviation of photon data and ACF is acquired by integration of 1 D function of distance variation. Fourier transform of ACF results in noise power spectrum which is called Wiener spectrum in image quality evaluation. Wiener spectrum represents noise itself. In addition, along with MTF, it is an important factor to produce detective quantum efficiency (DQE). The proposed evaluation method using Wiener spectrum is expected to contribute to educate the concept of Wiener spectrum in educational organizations, choose the appropriate imaging detectors for clinical applications, and maintain image quality in digital imaging systems.

• The Journal of Society for e-Business Studies
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• v.22 no.1
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• pp.37-49
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• 2017

In order to maximize the efficiency and the quality of care in a hospital, hospitals in general operate by appointments. Patient no-shows or missed appointments waste the time of staffs who prepare for appointments, deprive patients of needed care, and increase burden on clinic capacity. The purpose of this study is to examine the importance and significance of factors that affect patient no-shows. The actual data of 50,000 outpatient appointments is compiled and analyzed from a VAMC in the United States with aims to identify the factors that contribute to outpatient no-shows and to draw meaningful implications. Random forest along with logistic regression analysis identify the factors affecting no-shows; appointment leadtime, show-up rate, travel distance, no-show rate in previous period, patient age, severity, complexity of disease, chronic pain, depression, drug dependence. The appointment leadtime, show-up rate, travel distance and previous no-show rate can be improved by enhancing SMS pre-notification and by improving afterwards telephone counseling. For other factors, it needs to study on the service differentiation with the characteristics of each patient group.