• Knowledge Management Research
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• v.25 no.2
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• pp.19-47
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• 2024

Organizational ability to analyze and utilize data plays an important role in knowledge management and decision-making. This study aims to investigate the potential application of large language models in corporate data analysis. Focusing on the field of human resources, the research examines the data analysis capabilities of these models. Using the widely studied IBM HR dataset, the study reproduces machine learning-based employee turnover prediction analyses from previous research through ChatGPT and compares its predictive performance. Unlike past research methods that required advanced programming skills, ChatGPT-based machine learning data analysis, conducted through the analyst's natural language requests, offers the advantages of being much easier and faster. Moreover, its prediction accuracy was found to be competitive compared to previous studies. This suggests that large language models could serve as effective and practical alternatives in the field of corporate data analysis, which has traditionally demanded advanced programming capabilities. Furthermore, this approach is expected to contribute to the popularization of data analysis and the spread of data-driven decision-making (DDDM). The prompts used during the data analysis process and the program code generated by ChatGPT are also included in the appendix for verification, providing a foundation for future data analysis research using large language models.

• Journal of the Korean Society of Radiology
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• v.81 no.1
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• pp.157-165
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• 2020

Purpose To evaluate the optimal measurement location, cut-off value, and diagnostic performance of S-Shearwave in differential diagnosis of breast masses seen on ultrasonography (US). Materials and Methods During the study period, 225 breast masses in 197 women were included. S-Shearwave measurements were made by applying a square region-of-interest automatically generated by the US machine. Shearwave elasticity was measured three times at four different locations of the mass, and the highest shearwave elasticity was used for calculating the optimal cut-off value. Diagnostic performance was evaluated by using the area under the receiving operator characteristic curve (AUC). Results Of the 225 breast masses, 156 (69.3%) were benign and 69 (30.7%) were malignant. Mean S-Shearwave values were significantly higher for malignant masses (108.0 ± 70.0 kPa vs. 43.4 ± 38.3 kPa; p < 0.001). No significant differences were seen among AUC values at different measurement locations. With a cut-off value of 41.9 kPa, S-Shearwave showed 85.7% sensitivity, 63.9% specificity, 70.7% accuracy, and positive and negative predictive values of 51.7% and 90.8%, respectively. The AUCs for US and S-Shearwave did not show significant differences (p = 0.179). Conclusion S-Shearwave shows comparable diagnostic performance to that of grayscale US that can be applied for differential diagnosis of breast masses seen on US.

• Journal of Dental Rehabilitation and Applied Science
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• v.39 no.4
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• pp.276-284
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• 2023

After tooth extraction, alveolar bone is resorbed over time. Loss of alveolar bone and reduction of upper soft tissue poses difficulties in future implant placement and long-term survival of the implant. This case report focuses on increasing the soft and hard tissues at the implant placement site by using alveolar ridge augmentation and a xenogeneic collagen matrix as a soft tissue substitute in an extraction socket affected by periodontal disease. In each case, the width of the alveolar bone increased to 6 mm, 8 mm, and 4 mm, and regeneration of the interdental papilla around the implant was shown, as well as buccal keratinized gingiva of 4 mm, 6 mm, and 4 mm, respectively. Enlarged alveolar bone facilitates implant surgery, and interdental papillae and keratinized gingiva enable aesthetic prosthesis. This study performed alveolar ridge augmentation on patients with extraction sockets affected by periodontal disease and additionally used soft tissue substitutes to provide a better environment for implant placement and have positive effects for aesthetic and predictive implant surgery.

• Journal of Dental Rehabilitation and Applied Science
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• v.39 no.4
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• pp.250-259
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• 2023

The use of digital technology in fixed prosthetic treatment using implants enables predictive treatment through diagnosis and virtual surgery by integrating clinical and radiological information of patients. Existing digital scanning methods require several components to be removed, such as removing the healing abutment and connecting the scan body. In the scannable healing abutment developed in consideration of this point, scanning is performed directly on the healing abutment, maintaining soft tissue sealing and simplifying scanning. Digital technology can also be used when obtaining the intermaxillary relationship. Recently, various digital technologies have been reported to acquire the intermaxillary relationship of edentulous patients using surgical guides, patient-specific scanning devices, or scans of the inside of temporary dentures. In this case, the implant-supported fixed prosthesis treatment was performed through scanning the scannable healing abutment and the inner side of the temporary denture to obtain the intermaxillary relationship, thereby simplifying the treatment process and obtaining aesthetically and functionally excellent clinical results.

• Biomolecules & Therapeutics
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• v.32 no.1
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• pp.104-114
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• 2024

Licochalcone C (LCC; PubChem CID:9840805), a chalcone compound originating from the root of Glycyrrhiza inflata, has shown anticancer activity against skin cancer, esophageal squamous cell carcinoma, and oral squamous cell carcinoma. However, the therapeutic potential of LCC in treating colorectal cancer (CRC) and its underlying molecular mechanisms remain unclear. Chemotherapy for CRC is challenging because of the development of drug resistance. In this study, we examined the antiproliferative activity of LCC in human colorectal carcinoma HCT116 cells, oxaliplatin (Ox) sensitive and Ox-resistant HCT116 cells (HCT116-OxR). LCC significantly and selectively inhibited the growth of HCT116 and HCT116-OxR cells. An in vitro kinase assay showed that LCC inhibited the kinase activities of EGFR and AKT. Molecular docking simulations using AutoDock Vina indicated that LCC could be in ATP-binding pockets. Decreased phosphorylation of EGFR and AKT was observed in the LCC-treated cells. In addition, LCC induced cell cycle arrest by modulating the expression of cell cycle regulators p21, p27, cyclin B1, and cdc2. LCC treatment induced ROS generation in CRC cells, and the ROS induction was accompanied by the phosphorylation of JNK and p38 kinases. Moreover, LCC dysregulated mitochondrial membrane potential (MMP), and the disruption of MMP resulted in the release of cytochrome c into the cytoplasm and activation of caspases to execute apoptosis. Overall, LCC showed anticancer activity against both Ox-sensitive and Ox-resistant CRC cells by targeting EGFR and AKT, inducing ROS generation and disrupting MMP. Thus, LCC may be potential therapeutic agents for the treatment of Ox-resistant CRC cells.

• Korean Journal of Radiology
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• v.21 no.10
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• pp.1187-1195
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• 2020

Objective: This study aimed to determine the sonographic features suggestive of extrathyroidal extension (ETE) of thyroid cancers. Materials and Methods: We retrospectively reviewed the sonographic images of 1656 consecutive patients who had undergone thyroidectomy in 2017. The diagnostic performance of sonographic features suggestive of ETE was evaluated using operation and histopathologic reports. Sonographic features for gross ETE to the strap muscle and minor ETE were assessed for thyroid cancer abutting the anterolateral thyroid capsule. Sonographic features for tracheal invasion were assessed according to whether the angle between the tumor and the trachea was an acute, right, or obtuse angle. Sonographic features for recurrent laryngeal nerve (RLN) invasion were assessed based on the association between the tumor and tracheoesophageal groove (TEG) as preserved normal tissue, abutting or protruding into the TEG. Results: ETE was observed in 783 patients (47.3%), including 123 patients with gross ETE (7.4% [strap muscle, n = 97; RLN, n = 24; and trachea, n = 14]) and 660 patients with minor ETE (39.9%). Regarding the diagnosis of gross and minor ETE to the strap muscle, sonographic features of replacement of the strap muscle and capsular disruption showed the highest positive predictive value (75.9% and 58.5%, respectively). Thyroid cancer forming an obtuse angle with the trachea had the highest sensitivity for the diagnosis of tracheal invasion (85.7%), and thyroid cancer protrusion into the TEG showed the highest sensitivity for the diagnosis of RLN (83.3%). Conclusion: Sonography is considered beneficial in the diagnosis of ETE to the strap muscle, trachea, and RLN. Assessment of ETE is important for the accurate staging of thyroid cancer, which in turn determines the extent of surgery or whether active surveillance is appropriate or not.

• Korean Journal of Radiology
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• v.21 no.6
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• pp.670-683
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• 2020

Objective: The presence of coagulative necrosis (CN) in clear cell renal cell carcinoma (ccRCC) indicates a poor prognosis, while the absence of CN indicates a good prognosis. The purpose of this study was to build and validate a radiomics signature based on preoperative CT imaging data to estimate CN status in ccRCC. Materials and Methods: Altogether, 105 patients with pathologically confirmed ccRCC were retrospectively enrolled in this study and then divided into training (n = 72) and validation (n = 33) sets. Thereafter, 385 radiomics features were extracted from the three-dimensional volumes of interest of each tumor, and 10 traditional features were assessed by two experienced radiologists using triple-phase CT-enhanced images. A multivariate logistic regression algorithm was used to build the radiomics score and traditional predictors in the training set, and their performance was assessed and then tested in the validation set. The radiomics signature to distinguish CN status was then developed by incorporating the radiomics score and the selected traditional predictors. The receiver operating characteristic (ROC) curve was plotted to evaluate the predictive performance. Results: The area under the ROC curve (AUC) of the radiomics score, which consisted of 7 radiomics features, was 0.855 in the training set and 0.885 in the validation set. The AUC of the traditional predictor, which consisted of 2 traditional features, was 0.843 in the training set and 0.858 in the validation set. The radiomics signature showed the best performance with an AUC of 0.942 in the training set, which was then confirmed with an AUC of 0.969 in the validation set. Conclusion: The CT-based radiomics signature that incorporated radiomics and traditional features has the potential to be used as a non-invasive tool for preoperative prediction of CN in ccRCC.

• Korean Journal of Clinical Laboratory Science
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• v.55 no.4
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• pp.269-275
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• 2023

Echocardiography is a non-invasive method that is useful for diagnosing pulmonary arterial hypertension. It is known that echocardiography depends on the experience, education, and knowledge level of the cardiac sonographer. This study aimed to compare the agreement values between cardiac sonographer with different practical experiences in the diagnosis of pulmonary arterial hypertension using echocardiography. Three readers re-evaluated the echocardiography images of 148 patients who were diagnosed with pulmonary arterial hypertension at the S Medical Center from January 1, 2020, to December 31, 2020. The echocardiography values measured by each reader were compared and analyzed. The results of the analysis of discrete variables revealed that the agreement values of the cardiac sonographers showed excellent consistency for both reader 3 and the cardiologist group, indicating that more experience leads to better predictive accuracy for diagnosis of the condition. Furthermore, in terms of continuous variables, all the cardiac sonographer demonstrated good agreement in the measured values of the right atrium, which was easier to assess and clearer than the structurally complex measurements of the right ventricle. This study represents the first analysis in Korea of the agreement values measured by medical technologists who are cardiac sonographers.

• Journal of the Korean Society of Radiology
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• v.81 no.3
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• pp.610-619
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• 2020

Purpose The study aimed to investigate the role of Prostate Imaging Reporting and Data System version 2 (PI-RADS v2) in predicting incidental prostate cancer (PCa) or urothelial carcinoma (UCa) extension in urinary bladder (UB) cancer patients. Materials and Methods A total of 72 UB cancer patients who underwent radical cystoprostatectomy and 3 Tesla multiparametric MRI before surgery were enrolled. PI-RADS v2 ratings were assigned by two independent radiologists. All prostate specimens were examined by a single pathologist. We compared the multiparametric MRI findings rated using PI-RADS v2 with the pathologic data. Results Of the 72 UB cancer patients, 29 had incidental PCa (40.3%) and 20 showed UCa extension (27.8%), with an overlap for 3 patients. With a score of 4 as the cut-off value for predicting incidental PCa, the diagnostic accuracy was 65.3%, specificity was 90.7%, and positive predictive value (PPV) was 66.7%. The diagnostic accuracy for incidental UCa extension was 47.2%, specificity was 92.3%, and PPV was 83.3%. Conclusion Despite the low diagnostic accuracy, the PPV and specificity were relatively high. Therefore, PI-RADS v2 scores of 1, 2, or 3 may help exclude the probability of incidental PCa or UCa extension.

• Korean Journal of Radiology
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• v.25 no.4
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• pp.363-373
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• 2024

Objective: To develop and evaluate a deep learning model for automated segmentation and detection of bone metastasis on spinal MRI. Materials and Methods: We included whole spine MRI scans of adult patients with bone metastasis: 662 MRI series from 302 patients (63.5 ± 11.5 years; male:female, 151:151) from three study centers obtained between January 2015 and August 2021 for training and internal testing (random split into 536 and 126 series, respectively) and 49 MRI series from 20 patients (65.9 ± 11.5 years; male:female, 11:9) from another center obtained between January 2018 and August 2020 for external testing. Three sagittal MRI sequences, including non-contrast T1-weighted image (T1), contrast-enhanced T1-weighted Dixon fat-only image (FO), and contrast-enhanced fat-suppressed T1-weighted image (CE), were used. Seven models trained using the 2D and 3D U-Nets were developed with different combinations (T1, FO, CE, T1 + FO, T1 + CE, FO + CE, and T1 + FO + CE). The segmentation performance was evaluated using Dice coefficient, pixel-wise recall, and pixel-wise precision. The detection performance was analyzed using per-lesion sensitivity and a free-response receiver operating characteristic curve. The performance of the model was compared with that of five radiologists using the external test set. Results: The 2D U-Net T1 + CE model exhibited superior segmentation performance in the external test compared to the other models, with a Dice coefficient of 0.699 and pixel-wise recall of 0.653. The T1 + CE model achieved per-lesion sensitivities of 0.828 (497/600) and 0.857 (150/175) for metastases in the internal and external tests, respectively. The radiologists demonstrated a mean per-lesion sensitivity of 0.746 and a mean per-lesion positive predictive value of 0.701 in the external test. Conclusion: The deep learning models proposed for automated segmentation and detection of bone metastases on spinal MRI demonstrated high diagnostic performance.