• Health Policy and Management
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• v.24 no.1
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• pp.47-55
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• 2014

Background: Korea is considered to have an integrative health system where both western medicine and Korean (traditional) medicine are officially recognized and provided. Although Korean medicine has been covered by National Health Insurance over 20 years, equity in the utilization of Korean medical care has rarely been examined. Methods: We examined medical care utilization and expenditure of outpatient Korean medicine using panel fixed effects model to remove selection bias. Then we compared it with pooled ordinary least square (OLS) model. This study used Korea Health Panel data, which provides accurate information on out-of-pocket health care payment, including non-covered medical services. Results: Principal findings indicate that the frequency of the utilization of Korean medicine is related with unobservable individual choices different from western medicine, so the panel fixed effect model is appropriate. But pooled OLS model is better fitted for the expenditure of Korean medicine, after controlling for western medical care expenditure. After adjusting for the selection bias, socioeconomic status (income, education) was significantly associated with the expenditure of Korean medicine, but not with the frequency of the utilization of Korean medicine. Conclusion: This study shows that expenditure of Korean medicine utilization is inequitable across socioeconomic groups, which implies that health insurance coverage of Korean medicine is not sufficient.

• The Journal of Advanced Prosthodontics
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• v.12 no.1
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• pp.33-37
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• 2020

PURPOSE. The purpose of this study is to evaluate the effects of type of magnet attachment and implant angulation in two implant overdenture models. MATERIALS AND METHODS. Magnet attachments used in this study were flat and dome types (MGT5515, MGT5520D, Dentium Co., Seoul, Korea). Two implants with keepers were inserted in the resin blocks at a distance of 24 mm. For the first model, the implants were parallel to the vertical and perpendicular to the horizontal; for the second model, both were angulated 5 degrees to the mesial; for the third model, both were angulated 10 degrees toward the mesial. The retentive force was measured in both vertical and lateral directions. Statistical analyses were performed using SPSS software version 22.0 (α=.05). RESULTS. The flat type magnet attachment showed the highest lateral retentive force in the 20° divergent group (P<.05) and the dome type magnet attachment showed the highest lateral retentive force in the parallel group (P<.05). The vertical and lateral retentive force of the dome type magnet attachment was greater than that of the flat type magnet attachment in every direction (P<.05). CONCLUSION. Within the limitations of this study, the dome shape magnet attachment can resist vertical and lateral retentive force more superiorly than the flat type magnet attachment, regardless of angle, in the mandibular two implant model.

• Journal of Biomedical Engineering Research
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• v.41 no.5
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• pp.195-202
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• 2020

Needle detection in ultrasound images is sometimes difficult due to obstruction of fat tissues. Accurate needle detection using continuous ultrasound (CUS) images is a vital stage of treatment planning for tissue biopsy and brachytherapy. The main goal of the study is classified into two categories. First, new detection model, i.e. D-Attention Unet, is developed by combining the context information of 3D medical data and CUS images. Second, the D-Attention Unet model was compared with other models to verify its usefulness for needle detection in continuous ultrasound images. The continuous needle images taken with ultrasonic waves were converted into still images for dataset to evaluate the performance of the D-Attention Unet. The dataset was used for training and testing. Based on the results, the proposed D-Attention Unet model showed the better performance than other 3 models (Unet, D-Unet and Attention Unet), with Dice Similarity Coefficient (DSC), Recall and Precision at 71.9%, 70.6% and 73.7%, respectively. In conclusion, the D-Attention Unet model provides accurate needle detection for US-guided biopsy or brachytherapy, facilitating the clinical workflow. Especially, this kind of research is enthusiastically being performed on how to add image processing techniques to learning techniques. Thus, the proposed method is applied in this manner, it will be more effective technique than before.

• Journal of Physiology & Pathology in Korean Medicine
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• v.20 no.1
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• pp.196-201
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• 2006

Electroacupuncture(EA) is commonly used in various diseases. In the present study, the effect of EA in the allergic mouse model was examined. Allergy is generated via immunological mechanism and non-immunological mechanism. Mast cells activated dy those mechanisms get to release various substances such as histamine, leukotrienes, prostaglandin, TNF-$\alpha$, IL-4, IL-6, etc. which induce allergic reactions and the following inflammatory responses. To evaluate the anti-allergic effects of EA, mortality, ear swelling response, vascular permeability and cytokine secretion were investigated in EA group and non-EA group of which mice were compound 48/80-induced allergy model or PCA model. Compound 48/80 induces allergic reaction via non-immunological mechanism and PCA model is generated through the same mechanism with immediate-type(Type1) allergic reaction, one of immunological allergic reactions. EA inhibited compound 48/80-induced ear swelling response but did not inhibit the systemic anaphylaxis. EA also inhibited passive cutaneous anaphylaxis(PCA) activated dy anti-dinitrophenol IgE. In addition, EA inhibited IL-6 and TNF-$\alpha$ secretion from 48 h PCA in mice. These results indicate that EA may be used for the treatment of mast cell-mediated allergic diseases, especially immediate-type(Type 1) allergy and non-immunologically mediated allergy.

• Imaging Science in Dentistry
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• v.49 no.1
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• pp.19-26
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• 2019

Purpose: It has been proposed that using new prediction methods, such as neural networks based on dental data, could improve age estimation. This study aimed to assess the possibility of exploiting neural networks for estimating age by means of the pulp-to-tooth ratio in canines as a non-destructive, non-expensive, and accurate method. In addition, the predictive performance of neural networks was compared with that of a linear regression model. Materials and Methods: Three hundred subjects whose age ranged from 14 to 60 years and were well distributed among various age groups were included in the study. Two statistical software programs, SPSS 21 (IBM Corp., Armonk, NY, USA) and R, were used for statistical analyses. Results: The results indicated that the neural network model generally performed better than the regression model for estimation of age with pulp-to-tooth ratio data. The prediction errors of the developed neural network model were acceptable, with a root mean square error (RMSE) of 4.40 years and a mean absolute error (MAE) of 4.12 years for the unseen dataset. The prediction errors of the regression model were higher than those of the neural network, with an RMSE of 10.26 years and a MAE of 8.17 years for the test dataset. Conclusion: The neural network method showed relatively acceptable performance, with an MAE of 4.12 years. The application of neural networks creates new opportunities to obtain more accurate estimations of age in forensic research.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.5
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• pp.229-236
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• 2023

Since 3D printed medical implant parts usually have surface defects, it is necessary to inspect the surface after manufacturing. In order to automate the surface inspection, it is effective to 3D scan the implant and reconstruct it as a scan model such as a point cloud. When constructing a scan model, the characteristics of the shape and material of the implant must be considered because it has characteristics different from those of general 3D printed parts. In this paper, we present a method to reconstruct the 3D scan model of a 3D printed metal bone-plate that is one kind of medical implant parts. Multiple partial scan data are produced by multi-view 3D scan, and then, we reconstruct a scan model by alignment and merging of partial data. We also present the process of the scan model reconstruction through experiments.

• The Journal of Bigdata
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• v.6 no.1
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• pp.51-62
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• 2021

In the field of medical artificial intelligence, there have been a lot of researches on disease prediction and classification algorithms that can help doctors judge, but relatively less interested in artificial intelligence that can help medical consumers acquire and judge information. The fact that more than 150,000 questions have been asked about which hospital to go over the past year in NAVER portal will be a testament to the need to provide medical information suitable for medical consumers. Therefore, in this study, we wanted to establish a classification model that classifies 8 medical subjects for symptom text directly described by patients which was collected from NAVER portal to help consumers choose appropriate medical subjects for their symptoms. In order to ensure the validity of the data involving patients' subject matter, we conducted similarity measurements between objective symptom text (typical symptoms by medical subjects organized by the Seoul Emergency Medical Information Center) and subjective symptoms (NAVER data). Similarity measurements demonstrated that if the two texts were symptoms of the same medical subject, they had relatively higher similarity than symptomatic texts from different medical subjects. Following the above procedure, the classification model was constructed using a ridge regression model for subjective symptom text that obtained validity, resulting in an accuracy of 0.73.

• Korean Journal of Radiology
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• v.20 no.4
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• pp.641-648
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• 2019

Objective: The purpose of this study was to investigate whether three-dimensional (3D) magnetic resonance imaging could improve diagnostic accuracy for suspected posterior ligamentous complex (PLC) disruption. Materials and Methods: We used 20 freshly harvested goat spine samples with 60 segments and intact surrounding soft tissue. The animals were aged 1-1.5 years and consisted of 8 males and 12 females, which were sexually mature but had not reached adult weights. We created a paraspinal contusion model by percutaneously injecting 10 mL saline into each side of the interspinous ligament (ISL). All segments underwent T2-weighted sagittal and coronal short inversion time inversion recovery (STIR) scans as well as coronal and sagittal 3D proton density-weighted spectrally selective inversion recovery (3D-PDW-SPIR) scans acquired at 1.5T. Following scanning, some ISLs were cut and then the segments were rescanned using the same magnetic resonance (MR) techniques. Two radiologists independently assessed the MR images, and the reliability of ISL tear interpretation was assessed using the kappa coefficient. The chi-square test was used to compare the diagnostic accuracy of images obtained using the different MR techniques. Results: The interobserver reliability for detecting ISL disruption was high for all imaging techniques (0.776-0.949). The sensitivity, specificity, and diagnostic accuracy of the coronal 3D-PDW-SPIR technique for detecting ISL tears were 100, 96.9, and 97.9%, respectively, which were significantly higher than those of the sagittal STIR (p = 0.000), coronal STIR (p = 0.000), and sagittal 3D-PDW-SPIR (p = 0.001) techniques. Conclusion: Compared to other MR methods, coronal 3D-PDW-SPIR provides a more accurate diagnosis of ISL disruption. Adding coronal 3D-PDW-SPIR to a routine MR protocol may help to identify PLC disruptions in cases with nearby contusion.

• 대한핵의학회:학술대회논문집
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• 2004.11a
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• pp.414.2-414.2
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• 2004

• Journal of Korean Medical Ki-Gong Academy
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• v.12 no.1
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• pp.34-49
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• 2011

Objective : This research was carried out to find out the general understanding of korean medicine and the attitude toward medical gigong among common people. Methods : Randomly selected 297 people participated in this research. We performed this survey with 13 items on the Questionnaire Results : 13.1% of respondents knew qigong training, and 7.1% of respondents knew medical qigong. Most respondents knew one or more terms of qigong. Among them, the order was known as meridian, danjeon, sojucheon. 57.6% of respondents had a mind to be in a treatment of medical qigong. And 45.7% of respondents were satisfied with the harmless of medical gigong. However, 41% were unsatisfied with the low effect of the treatment. Conclusions : Medical gigong treatment need to develop an explanatory model which based on static study. And technically advanced public relations are needed.