• Journal of Yeungnam Medical Science
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• v.24 no.2
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• pp.97-106
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• 2007

Functional electrical stimulation (FES) has developed over the last 35 years to become a scientifically, technologically and clinically recognized field of interest in clinical medicine. FES has been applied to locomotion, grasping, ventilation, incontinence, and decubitus healing. However, all of these achievements illustrate the initial applications of FES; its true potential has not yet been realized. Recently, FES systems, which are miniaturized stimulation devices, have been utilized in the clinical setting. However, because the stimulating electrodes of the current FES devices are percutaneous electrodes, which are susceptible to wire breakage, and skin infection an implantable FES stimulating electrode has been introduced in the U.S. and Japan. In the present study, an external power supply method using radio frequency (RF) coupling and data transmission was developed for the control of the implantable FES device. In addition, we review the current understanding of FES devices and their application in clinical medicine.

• Korean Journal of Digital Imaging in Medicine
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• v.10 no.2
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• pp.33-37
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• 2008

To keep the online medical records available to anyone without constraint of time and space, introducing EMR (Electronic medical record), which is a clinical support management system. The purpose of this study is to develop interface standard of clinical test device. Integration and sharing of medical information is faced with enormous obstacles because medical organizations and associated companies are separately developing the interface. I hope that multi-function management system with workstation concept is operated to efficiently transmit clinical device result data based on this study. Transfer of precise medical result data available for decision making will improve quality of health care service.

• Communications for Statistical Applications and Methods
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• v.18 no.2
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• pp.179-187
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• 2011

The purpose of a Phase I clinical trial is to estimate the maximum tolerated dose, MTD, of a new drug. In this paper, the MTD estimation method is suggested by curve fitting the dose-toxicity data to an S-shaped curve. The suggested MTD estimation method is compared with established MTD estimation procedures using a Monte Carlo simulation study.

• Journal of Internet Computing and Services
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• v.18 no.5
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• pp.55-60
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• 2017

The pulmonary function test (PFT) is an essential data source for evaluating the effect of drugs on the lungs or the status of lung function. However, the numeric values of PFT cannot be easily used for clinical studies without labor-intensive manual efforts, because PFTs are usually recorded as image files. This study was aimed at constructing a de-identified, open-access PFT database with various clinical information. For constructing the PFT database, optical character recognition (OCR), regular expression, and the parsing technique were used to extract alphanumeric data from the PFT images in a Korean tertiary teaching hospital. This longitudinal observational database contains 413,000 measurements of PFT from 183,000 patients.

• Restorative Dentistry and Endodontics
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• v.28 no.1
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• pp.34-40
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• 2003

Chewing simulator, which can partly mimic the motion of chewing motion of human, has been successfully developed. The purpose of its development was to make a new machine which can anticipate the clinical results of restoration in the human teeth more accurately in vitro condition It is composed of 4 major parts, chewing part, motor part, water bath, controlling part. The controlling part control the chewing force, frequency, the temperature and running time of water. Additionally, the actual chewing force and remaining time is shown in the monitor of controlling part. At present, the chewing cycle is composed depending on the pre-published data of foreign people. Long term clinical data should be additionally collected for the simulator to mimic the clinical results more accurately.

• Fibers and Polymers
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• v.6 no.1
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• pp.49-54
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• 2005

The purpose of this study has been to investigate the effect of dilation on the some mechanical properties of several types of warp-knitted vascular grafts. The structures of warp knit vascular grafts used in the experiments were reverse locknit, locknit, and Tricot. Various mechanical properties of these grafts were determined using devices developed for the purpose. Clinical data obtained were compared with experimental results of warp knit vascular grafts. The most important mechanical properties are found to be creep extension, bursting strengths, and compliance. Preliminary results indicate that vascular grafts are non-compliant and exhibit creep which is predictive of the long term dilation that has been noted in the clinical results. It is found that there is a positive correlation between experimental data and clinical results for at least the grafts tested.

• Journal of the Korean Data and Information Science Society
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• v.21 no.6
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• pp.1343-1351
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• 2010

Sample size determination is very important part in clinical trials because it influences the time and the cost of the experimental studies. In this article, we consider the Bayesian methods for sample size determination based on hypothesis testing. Specifically we compare the usual Bayesian method using Bayes factor with the decision theoretic method using Bayesian reference criterion in mean difference problem for the normal case with known variances. We illustrate two procedures numerically as well as graphically.

• Clinical and Experimental Pediatrics
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• v.64 no.4
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• pp.157-164
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• 2021

Since the emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in December 2019, a small number of coronavirus disease 2019 (COVID-19) cases in neonates have been reported worldwide. Neonates currently account for only a minor proportion of the pediatric population affected by COVID-19. Thus, data on the epidemiological and clinical features of COVID-19 in neonates are limited. Approximately 3% of neonates born to mothers with COVID-19 reportedly tested positive for SARS-CoV-2. Current limited data on neonates with COVID-19 suggest that neonatal COVID-19 shows a relatively benign course despite a high requirement for mechanical ventilation. However, neonates with pre-existing medical conditions and preterm infants appear to be at a higher risk of developing severe COVID-19. The greatest perinatal concern of the COVID-19 pandemic is the possibility of vertical transmission, especially transplacental transmission of SARS-CoV-2. Although direct evidence of the vertical transmission of SARS-CoV-2 is lacking, its possibility during late pregnancy cannot be ruled out. This review summarizes available case studies on COVID-19 in neonates and introduces what is currently known about neonatal COVID-19 with focus on its vertical transmission.

• Journal of Korean Academy of Dental Administration
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• v.8 no.1
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• pp.24-29
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• 2020

With the advancement of information technology, the application of augmented reality (AR) in dentistry is an emerging research field of image-guided surgery and dental education. In addition, the digital approach to incorporating AR in dental practice management is considered to be feasible. A prototype is developed to apply AR to dental daily clinical practice in order to help dentists to access electronic dental records. This prototype delivers patients' information and related clinical data to dental clinicians directly without the need to search for the appropriate patients. Wearable AR devices are considered to be a convenient tool for practicing dentists because dental practitioners are not always able to use a computer during active clinical sessions, such as implant placement, root canal treatment, and patient-doctor communication. The use of AR to visualize passive transferred patient data would be valuable for practicing dentists.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.05a
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• pp.539-541
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• 2023

COVID-19 is a viral pandemic disease that spreads widely all around the world. The only way to identify COVID-19 patients at an early stage is to stop the spread of the virus. Different approaches are used to diagnose, such as RT-PCR, Chest X-rays, and CT images. However, these are time-consuming and require a specialized lab. Therefore, there is a need to develop a time-efficient diagnosis method to detect COVID-19 patients. The proposed machine learning (ML) approach predicts the presence of coronavirus based on clinical symptoms. The clinical dataset is collected from the Israeli Ministry of Health. We used different ML classifiers (i.e., XGB, DT, RF, and NB) to diagnose COVID-19. Later, classifiers are optimized with the Bayesian hyperparameter optimization approach to improve the performance. The optimized RF outperformed the others and achieved an accuracy of 97.62% on the testing data that help the early diagnosis of COVID-19 patients.