• Korean Journal of Radiology
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• v.23 no.11
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• pp.1078-1088
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• 2022

Objective: To develop and validate a model using radiomics features from apparent diffusion coefficient (ADC) map to diagnose local tumor recurrence in head and neck squamous cell carcinoma (HNSCC). Materials and Methods: This retrospective study included 285 patients (mean age ± standard deviation, 62 ± 12 years; 220 male, 77.2%), including 215 for training (n = 161) and internal validation (n = 54) and 70 others for external validation, with newly developed contrast-enhancing lesions at the primary cancer site on the surveillance MRI following definitive treatment of HNSCC between January 2014 and October 2019. Of the 215 and 70 patients, 127 and 34, respectively, had local tumor recurrence. Radiomics models using radiomics scores were created separately for T2-weighted imaging (T2WI), contrast-enhanced T1-weighted imaging (CE-T1WI), and ADC maps using non-zero coefficients from the least absolute shrinkage and selection operator in the training set. Receiver operating characteristic (ROC) analysis was used to evaluate the diagnostic performance of each radiomics score and known clinical parameter (age, sex, and clinical stage) in the internal and external validation sets. Results: Five radiomics features from T2WI, six from CE-T1WI, and nine from ADC maps were selected and used to develop the respective radiomics models. The area under ROC curve (AUROC) of ADC radiomics score was 0.76 (95% confidence interval [CI], 0.62-0.89) and 0.77 (95% CI, 0.65-0.88) in the internal and external validation sets, respectively. These were significantly higher than the AUROC values of T2WI (0.53 [95% CI, 0.40-0.67], p = 0.006), CE-T1WI (0.53 [95% CI, 0.40-0.67], p = 0.012), and clinical parameters (0.53 [95% CI, 0.39-0.67], p = 0.021) in the external validation set. Conclusion: The radiomics model using ADC maps exhibited higher diagnostic performance than those of the radiomics models using T2WI or CE-T1WI and clinical parameters in the diagnosis of local tumor recurrence in HNSCC following definitive treatment.

• Korean Journal of Radiology
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• v.23 no.12
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• pp.1281-1289
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• 2022

Objective: Radiomic modeling using multiple regions of interest in MRI of the brain to diagnose juvenile myoclonic epilepsy (JME) has not yet been investigated. This study aimed to develop and validate radiomics prediction models to distinguish patients with JME from healthy controls (HCs), and to evaluate the feasibility of a radiomics approach using MRI for diagnosing JME. Materials and Methods: A total of 97 JME patients (25.6 ± 8.5 years; female, 45.5%) and 32 HCs (28.9 ± 11.4 years; female, 50.0%) were randomly split (7:3 ratio) into a training (n = 90) and a test set (n = 39) group. Radiomic features were extracted from 22 regions of interest in the brain using the T1-weighted MRI based on clinical evidence. Predictive models were trained using seven modeling methods, including a light gradient boosting machine, support vector classifier, random forest, logistic regression, extreme gradient boosting, gradient boosting machine, and decision tree, with radiomics features in the training set. The performance of the models was validated and compared to the test set. The model with the highest area under the receiver operating curve (AUROC) was chosen, and important features in the model were identified. Results: The seven tested radiomics models, including light gradient boosting machine, support vector classifier, random forest, logistic regression, extreme gradient boosting, gradient boosting machine, and decision tree, showed AUROC values of 0.817, 0.807, 0.783, 0.779, 0.767, 0.762, and 0.672, respectively. The light gradient boosting machine with the highest AUROC, albeit without statistically significant differences from the other models in pairwise comparisons, had accuracy, precision, recall, and F1 scores of 0.795, 0.818, 0.931, and 0.871, respectively. Radiomic features, including the putamen and ventral diencephalon, were ranked as the most important for suggesting JME. Conclusion: Radiomic models using MRI were able to differentiate JME from HCs.

• Information Systems Review
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• v.20 no.4
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• pp.43-57
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• 2018

We propose network effects upon the investment decision of cloud-based ERP. Using the survey data collected from 82 companies in 2015, we examine whether IT managers have an intention to adopt real options in order to manage the risk of cloud-based ERP investments and how the network effects influence upon the intention to adopt real options. Based on prior literature, we propose a research model with 4 hypotheses. We find partial support of the hypotheses from the empirical analysis: technological risks has a positive impact upon the adoption of real options such as defer, contract, and abandon. In contrast, we find no significant impact of security risks upon real options. We validate positive network effects upon the adoption of real options such as defer, contract, and abandon. This work empirically find that IT managers in Korean middle and small sized firms have an intention to adopt real options when the managers realize economic, technological, and relationship risks and when they expect network effects.

• Journal of the Korea Society of Computer and Information
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• v.29 no.5
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• pp.111-121
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• 2024

With strength training comes the risk of injury and the benefits of exercise. Lack of knowledge and experience or repetitions at excessive intensity can lead to injury. Adequate feedback on an exercise's progress can increase the exercise's effectiveness and reduce injuries by providing scientific data and psychological motivation. This study aimed to validate EMG equipment and examine the effects of 8 weeks of biofeedback training with wireless electromyography. A correlation analysis between the Noraxon device and Fitsig^®(EMG Prototype), a well-known instrument in the field of research, showed a moderate correlation. Statistically significant differences in humeral circumference, humeral muscle mass, and biceps and triceps strength were found between the left and right sides of the body over time, with no differences in the type of exercise. Feedback training with real-time EMG was found to be favorable for hypertrophic growth and strength improvement. Future studies should be conducted to investigate its application in sports activities further.

• Annals of Occupational and Environmental Medicine
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• v.35
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• pp.22.1-22.9
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• 2023

Background: Shift work increases the risk of chronic diseases, including metabolic diseases. However, studies on the relationship between shift work and renal function are limited. The aim of this study was to investigate the association between shift work and a decreased glomerular filtration rate (GFR). Methods: Data were evaluated for 1,324,930 workers who visited the Korean Medical Institute from January 1, 2016 to December 31, 2020 and underwent a health checkup. Daytime workers were randomly extracted at a ratio of 1:4 after matching for age and sex. In total, 18,190 workers aged over 40 years were included in the analyses; these included 3,638 shift workers and 14,552 daytime workers. Participants were categorized into the shift work group when they underwent a specific health checkup for night shift work or indicated that they were shift workers in the questionnaire. The odds ratio was calculated using a conditional logistic regression to investigate the relevance of shift work for changes in GFR. Results: 35 workers in the shift group and 54 in the daytime group exhibited an estimated GFR (eGFR) value of < 60 mL/min/1.73m² (p < 0.01). The difference in eGFR values between two checkups differed significantly depending on the type of work (p < 0.01); the difference in the shift work group (-9.64 mL/min/1.73 m²) was larger than that in the daytime work group (-7.45 mL/min/1.73 m²). The odds ratio for eGFR reduction to < 60 mL/min/1.73 m² in the shift group versus the daytime group was 4.07 (95% confidence interval: 2.54-6.52), which was statistically significant. Conclusions: The results of this study suggest that eGFR decreases by a significantly larger value in shift workers than in daytime workers; thus, shift work could be a contributing factor for chronic kidney disease (CKD). Further prospective studies are necessary to validate this finding and identify measures to prevent CKD in shift workers.

• International Journal of Stem Cells
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• v.16 no.4
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• pp.425-437
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• 2023

Obesity, which continues to increase worldwide, was shown to irreversibly impair the differentiation potential and angiogenic properties of adipose tissue mesenchymal stromal cells (ADSCs). Because these cells are intended for regenerative medicine, especially for the treatment of inflammatory conditions, and the effects of obesity on the immunomodulatory properties of ADSCs are not yet clear, here we investigated how ADSCs isolated from former obese subjects (Ex-Ob) would influence macrophage differentiation and polarization, since these cells are the main instructors of inflammatory responses. Analysis of the subcutaneous adipose tissue (SAT) of overweight (OW) and Ex-Ob subjects showed the maintenance of approximately twice as many macrophages in Ex-Ob SAT, contained within the CD68⁺/FXIII-A^- inflammatory pool. Despite it, in vitro, coculture experiments revealed that Ex-Ob ADSCs instructed monocyte differentiation into a M2-like profile, and under inflammatory conditions induced by LPS treatment, inhibited HLA-DR upregulation by resting M0 macrophages, originated a similar percentage of TNF-α⁺ cells, and inhibited IL-10 secretion, similar to OW-ADSCs and BMSCs, which were used for comparison, as these are the main alternative cell types available for therapeutic purposes. Our results showed that Ex-Ob ADSCs mirrored OW-ADSCs in macrophage education, favoring the M2 immunophenotype and a mixed (M1/M2) secretory response. These results have translational potential, since they provide evidence that ADSCs from both Ex-Ob and OW subjects can be used in regenerative medicine in eligible therapies. Further in vivo studies will be fundamental to validate these observations.

• Journal of Korean Tunnelling and Underground Space Association
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• v.25 no.6
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• pp.569-582
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• 2023

In recent years, the service life of major SOC facilities in south korea has exceeded 30 years, and rapid aging is expected within the next 10 years. This has led to a growing recognition of the need for proactive maintenance of these facilities. Consequently, there have been numerous research efforts to introduce smart inspection technologies into maintenance. However, the current system relies primarily on manpower for safety inspections and diagnostics, and on-site surveys rely on visual inspections. Manpower inspections can be time-consuming, and subjective errors may occur during result analysis. In the case of tunnels, there are disadvantages, such as the loss of social overhead capital due to partial closures during inspections. Therefore, institutionalizing smart safety inspections is essential, considering specific measures like using advanced equipment and updating qualifications for experts. Furthermore, it is necessary to verify and validate safety inspection results using advanced equipment before instituting changes. This could be achieved through national-level official research programs and the operation of verification and validation institutions. If smart inspection technology is introduced into maintenance, routine inspections of SOC facilities, such as tunnels, will become feasible. As a result, maintenance technology capable of early detection and proactive response to safety incidents caused by changes in facility conditions is anticipated.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.2
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• pp.35-40
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• 2024

In this paper, we validate the practicality of the OnePIC app implemented in the previous study by analyzing the execution and storage performance. The OnePIC app is a camera app that allows you to get a photo with a desired focus after taking photos focused on various places. To evaluate performance, we analyzed distance focus shooting time and object focus shooting time in detail. The performance evaluation was measured on actual smartphone. Distance focus shooting time for 5 photos was around 0.84 seconds, the object detection time was around 0.19 seconds regardless of the number of objects and object focus shooting time for 5 photos was around 4.84 seconds. When we compared the size of a single All-in-JPEG file that stores multi-focus photos to the size of the JPEG files stored individually, there was no significant benefit in storage space because the All-in-JPEG file size was subtly reduced. However, All-in-JPEG has the great advantage of managing multi-focus photos. Finally, we conclude that the OnePIC app is practical in terms of shooting time, photo storage size, and management.

• Journal of the Korean Applied Science and Technology
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• v.41 no.2
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• pp.459-471
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• 2024

In modern society, where tension and stress are ubiquitous, individuals often experience psychological imbalances. These stressors not only affect mental well-being but also manifest physically, through the skin. Consequently, a new term psychodermatology combining psychiatry and dermatology, has emerged, garnerning attention and research focus. In this study, we aimed to develop materials improving chronic skin conditions caused by stress by utilizing a compound of Cucurbita moschata, Paeonia japonica, and Prunus cerasus known to alleviate skin disorders. We sought to develop and validate the efficacy of materials alleviating chronic skin conditions induced by stress in keratinocytes..Therefore, in this study we analyzed the effects of a complex extract using Cucurbita moschata, Paeonia japonica, and Prunus cerasus on HaCaT keratinocyte cells to understand how it influences them. The complex extract on HaCaT keratinocyte cells showed a concentration-dependent decrease in the expression levels of TNF-α, IL-1β, IL-6, MDC, and TARC at concentrations of 12.5, 25, 50 and 100 ㎍/mL. Particularly noteworthy was the efficacy observed in inhibiting IL-1β, with a reduction of over 40% at a concentration of 100 ㎍/mL. Additionally, the production levels of AQP-3, HA, and filaggrin exhibited a significant concentration-dependent increase. The protein expression of p-ERK, p-JNK, and p-p38, which were elevated by TNF-α/IFN-γ, was significantly decreased with the treatment of the complex extract. These findings suggest that the compound extract may be utilized as a material for treating and preventing skin conditions, potentially mitigating the adverse effects of the mutual relationship between skin disorders and stress.

• Korean Journal of Radiology
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• v.21 no.8
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• pp.987-997
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• 2020

Objective: Measurement of the liver and spleen volumes has clinical implications. Although computed tomography (CT) volumetry is considered to be the most reliable noninvasive method for liver and spleen volume measurement, it has limited application in clinical practice due to its time-consuming segmentation process. We aimed to develop and validate a deep learning algorithm (DLA) for fully automated liver and spleen segmentation using portal venous phase CT images in various liver conditions. Materials and Methods: A DLA for liver and spleen segmentation was trained using a development dataset of portal venous CT images from 813 patients. Performance of the DLA was evaluated in two separate test datasets: dataset-1 which included 150 CT examinations in patients with various liver conditions (i.e., healthy liver, fatty liver, chronic liver disease, cirrhosis, and post-hepatectomy) and dataset-2 which included 50 pairs of CT examinations performed at ours and other institutions. The performance of the DLA was evaluated using the dice similarity score (DSS) for segmentation and Bland-Altman 95% limits of agreement (LOA) for measurement of the volumetric indices, which was compared with that of ground truth manual segmentation. Results: In test dataset-1, the DLA achieved a mean DSS of 0.973 and 0.974 for liver and spleen segmentation, respectively, with no significant difference in DSS across different liver conditions (p = 0.60 and 0.26 for the liver and spleen, respectively). For the measurement of volumetric indices, the Bland-Altman 95% LOA was -0.17 ± 3.07% for liver volume and -0.56 ± 3.78% for spleen volume. In test dataset-2, DLA performance using CT images obtained at outside institutions and our institution was comparable for liver (DSS, 0.982 vs. 0.983; p = 0.28) and spleen (DSS, 0.969 vs. 0.968; p = 0.41) segmentation. Conclusion: The DLA enabled highly accurate segmentation and volume measurement of the liver and spleen using portal venous phase CT images of patients with various liver conditions.