Recently, attempts have been made to convert unstructured text into vectors and to analyze vast amounts of natural language for various purposes. In particular, the demand for analyzing texts in specialized domains is rapidly increasing. Therefore, studies are being conducted to analyze specialized and general-purpose documents simultaneously. To analyze specific terms with general terms, it is necessary to align the embedding space of the specific terms with the embedding space of the general terms. So far, attempts have been made to align the embedding of specific terms into the embedding space of general terms through a transformation matrix or mapping function. However, the linear transformation based on the transformation matrix showed a limitation in that it only works well in a local range. To overcome this limitation, various types of nonlinear vector alignment methods have been recently proposed. We propose a vector alignment model that matches the embedding space of specific terms to the embedding space of general terms through end-to-end learning that simultaneously learns the autoencoder and regression model. As a result of experiments with R&D documents in the "Healthcare" field, we confirmed the proposed methodology showed superior performance in terms of accuracy compared to the traditional model.
Heerin Lee;Sung Hun Kim;Bong joo Kang;Jeong Min Lee
Journal of the Korean Society of Radiology
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v.83
no.4
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pp.876-886
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2022
Purpose To evaluate the performance of MicroPure US imaging to detect and characterize microcalcifications. Materials and Methods A total of 171 lesions with suspicious microcalcifications seen on mammography and B-mode US were included and simultaneously evaluated using MicroPure US imaging. The size of microcalcifications was divided into small (punctate, amorphous, fine pleomorphic, and fine linear) and large (coarse heterogeneous), and the extent was divided into narrow (grouped) and wide (others). MicroPure US imaging visibility was divided into four types based on the number of microcalcifications on the two images: B > M (more on B-mode), B = M (similar), B < M (more on MicroPure), and negative. Triple pairwise comparison was used to evaluate the imaging features according to the MicroPure US imaging visibility. Results Among the 171 lesions examined, 157 lesions (91.8%) were detected by MicroPure US imaging. The proportion of Breast Imaging Reporting and Data System (BI-RADS) category 4A was significantly higher in the MicroPure positive group, and that of category 4B was significantly higher in the MicroPure negative group (p = 0.035). The other imaging features did not differ. Among the positive MicroPure subgroups, all features showed no significant difference. Conclusion MicroPure US imaging demonstrated 91.8% positivity in detecting microcalcifications on B-mode US. MicroPure US imaging visibility correlated with the BI-RADS category of microcalcifications.
Koung Mi Kang;Kyung Min Kim;In Seong Kim;Joo Hyun Kim;Ho Kang;So Young Ji;Yun-Sik Dho;Hyongmin Oh;Hee-Pyoung Park;Han Gil Seo;Sung-Min Kim;Seung Hong Choi;Chul-Kee Park
Korean Journal of Radiology
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v.24
no.6
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pp.553-563
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2023
Objective: Functional magnetic resonance imaging (fMRI) and diffusion tensor imaging-derived tractography (DTI-t) contribute to the localization of language areas, but their accuracy remains controversial. This study aimed to investigate the diagnostic performance of preoperative fMRI and DTI-t obtained with a simultaneous multi-slice technique using intraoperative direct cortical stimulation (DCS) or corticocortical evoked potential (CCEP) as reference standards. Materials and Methods: This prospective study included 26 patients (23-74 years; male:female, 13:13) with tumors in the vicinity of Broca's area who underwent preoperative fMRI and DTI-t. A site-by-site comparison between preoperative (fMRI and DTI-t) and intraoperative language mapping (DCS or CCEP) was performed for 226 cortical sites to calculate the sensitivity and specificity of fMRI and DTI-t for mapping Broca's areas. For sites with positive signals on fMRI or DTI-t, the true-positive rate (TPR) was calculated based on the concordance and discordance between fMRI and DTI-t. Results: Among 226 cortical sites, DCS was performed in 100 sites and CCEP was performed in 166 sites. The specificities of fMRI and DTI-t ranged from 72.4% (63/87) to 96.8% (122/126), respectively. The sensitivities of fMRI (except for verb generation) and DTI-t were 69.2% (9/13) to 92.3% (12/13) with DCS as the reference standard, and 40.0% (16/40) or lower with CCEP as the reference standard. For sites with preoperative fMRI or DTI-t positivity (n = 82), the TPR was high when fMRI and DTI-t were concordant (81.2% and 100% using DCS and CCEP, respectively, as the reference standards) and low when fMRI and DTI-t were discordant (≤ 24.2%). Conclusion: fMRI and DTI-t are sensitive and specific for mapping Broca's area compared with DCS and specific but insensitive compared with CCEP. A site with a positive signal on both fMRI and DTI-t represents a high probability of being an essential language area.
So Hyun Park;Subin Heo;Bohyun Kim;Jungbok Lee;Ho Joong Choi;Pil Soo Sung;Joon-Il Choi
Korean Journal of Radiology
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v.24
no.3
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pp.190-203
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2023
Objective: We aimed to assess and validate the radiologic and clinical factors that were associated with recurrence and survival after curative surgery for heterogeneous targetoid primary liver malignancies in patients with chronic liver disease and to develop scoring systems for risk stratification. Materials and Methods: This multicenter retrospective study included 197 consecutive patients with chronic liver disease who had a single targetoid primary liver malignancy (142 hepatocellular carcinomas, 37 cholangiocarcinomas, 17 combined hepatocellular carcinoma-cholangiocarcinomas, and one neuroendocrine carcinoma) identified on preoperative gadoxetic acid-enhanced MRI and subsequently surgically removed between 2010 and 2017. Of these, 120 patients constituted the development cohort, and 77 patients from separate institution served as an external validation cohort. Factors associated with recurrence-free survival (RFS) and overall survival (OS) were identified using a Cox proportional hazards analysis, and risk scores were developed. The discriminatory power of the risk scores in the external validation cohort was evaluated using the Harrell C-index. The Kaplan-Meier curves were used to estimate RFS and OS for the different risk-score groups. Results: In RFS model 1, which eliminated features exclusively accessible on the hepatobiliary phase (HBP), tumor size of 2-5 cm or > 5 cm, and thin-rim arterial phase hyperenhancement (APHE) were included. In RFS model 2, tumors with a size of > 5 cm, tumor in vein (TIV), and HBP hypointense nodules without APHE were included. The OS model included a tumor size of > 5 cm, thin-rim APHE, TIV, and tumor vascular involvement other than TIV. The risk scores of the models showed good discriminatory performance in the external validation set (C-index, 0.62-0.76). The scoring system categorized the patients into three risk groups: favorable, intermediate, and poor, each with a distinct survival outcome (all log-rank p < 0.05). Conclusion: Risk scores based on rim arterial enhancement pattern, tumor size, HBP findings, and radiologic vascular invasion status may help predict postoperative RFS and OS in patients with targetoid primary liver malignancies.
Objective: This study aimed to develop and validate models using radiomics features on a native T1 map from cardiac magnetic resonance (CMR) to predict left ventricular reverse remodeling (LVRR) in patients with nonischemic dilated cardiomyopathy (NIDCM). Materials and Methods: Data from 274 patients with NIDCM who underwent CMR imaging with T1 mapping at Severance Hospital between April 2012 and December 2018 were retrospectively reviewed. Radiomic features were extracted from the native T1 maps. LVRR was determined using echocardiography performed ≥ 180 days after the CMR. The radiomics score was generated using the least absolute shrinkage and selection operator logistic regression models. Clinical, clinical + late gadolinium enhancement (LGE), clinical + radiomics, and clinical + LGE + radiomics models were built using a logistic regression method to predict LVRR. For internal validation of the result, bootstrap validation with 1000 resampling iterations was performed, and the optimism-corrected area under the receiver operating characteristic curve (AUC) with 95% confidence interval (CI) was computed. Model performance was compared using AUC with the DeLong test and bootstrap. Results: Among 274 patients, 123 (44.9%) were classified as LVRR-positive and 151 (55.1%) as LVRR-negative. The optimism-corrected AUC of the radiomics model in internal validation with bootstrapping was 0.753 (95% CI, 0.698-0.813). The clinical + radiomics model revealed a higher optimism-corrected AUC than that of the clinical + LGE model (0.794 vs. 0.716; difference, 0.078 [99% CI, 0.003-0.151]). The clinical + LGE + radiomics model significantly improved the prediction of LVRR compared with the clinical + LGE model (optimism-corrected AUC of 0.811 vs. 0.716; difference, 0.095 [99% CI, 0.022-0.139]). Conclusion: The radiomic characteristics extracted from a non-enhanced T1 map may improve the prediction of LVRR and offer added value over traditional LGE in patients with NIDCM. Additional external validation research is required.
Xu Yang;Xia Lu;Jun Liu;Ying Kan;Wei Wang;Shuxin Zhang;Lei Liu;Jixia Li;Jigang Yang
Korean Journal of Radiology
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v.23
no.4
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pp.466-478
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2022
Objective: 18F-fluorodeoxyglucose (FDG) PET/CT is often used for detecting malignancy in patients with newly diagnosed hemophagocytic lymphohistiocytosis (HLH), with acceptable sensitivity but relatively low specificity. The aim of this study was to improve the diagnostic ability of 18F-FDG PET/CT in identifying malignancy in patients with HLH by combining 18F-FDG PET/CT and clinical parameters. Materials and Methods: Ninety-seven patients (age ≥ 14 years) with secondary HLH were retrospectively reviewed and divided into the derivation (n = 71) and validation (n = 26) cohorts according to admission time. In the derivation cohort, 22 patients had malignancy-associated HLH (M-HLH) and 49 patients had non-malignancy-associated HLH (NM-HLH). Data on pretreatment 18F-FDG PET/CT and laboratory results were collected. The variables were analyzed using the Mann-Whitney U test or Pearson's chi-square test, and a nomogram for predicting M-HLH was constructed using multivariable binary logistic regression. The predictors were also ranked using decision-tree analysis. The nomogram and decision tree were validated in the validation cohort (10 patients with M-HLH and 16 patients with NM-HLH). Results: The ratio of the maximal standardized uptake value (SUVmax) of the lymph nodes to that of the mediastinum, the ratio of the SUVmax of bone lesions or bone marrow to that of the mediastinum, and age were selected for constructing the model. The nomogram showed good performance in predicting M-HLH in the validation cohort, with an area under the receiver operating characteristic curve of 0.875 (95% confidence interval, 0.686-0.971). At an appropriate cutoff value, the sensitivity and specificity for identifying M-HLH were 90% (9/10) and 68.8% (11/16), respectively. The decision tree integrating the same variables showed 70% (7/10) sensitivity and 93.8% (15/16) specificity for identifying M-HLH. In comparison, visual analysis of 18F-FDG PET/CT images demonstrated 100% (10/10) sensitivity and 12.5% (2/16) specificity. Conclusion: 18F-FDG PET/CT may be a practical technique for identifying M-HLH. The model constructed using 18F-FDG PET/CT features and age was able to detect malignancy with better accuracy than visual analysis of 18F-FDG PET/CT images.
Objective: T1 mapping provides valuable information regarding cardiomyopathies. Manual drawing is time consuming and prone to subjective errors. Therefore, this study aimed to test a DL algorithm for the automated measurement of native T1 and extracellular volume (ECV) fractions in cardiac magnetic resonance (CMR) imaging with a temporally separated dataset. Materials and Methods: CMR images obtained for 95 participants (mean age ± standard deviation, 54.5 ± 15.2 years), including 36 left ventricular hypertrophy (12 hypertrophic cardiomyopathy, 12 Fabry disease, and 12 amyloidosis), 32 dilated cardiomyopathy, and 27 healthy volunteers, were included. A commercial deep learning (DL) algorithm based on 2D U-net (Myomics-T1 software, version 1.0.0) was used for the automated analysis of T1 maps. Four radiologists, as study readers, performed manual analysis. The reference standard was the consensus result of the manual analysis by two additional expert readers. The segmentation performance of the DL algorithm and the correlation and agreement between the automated measurement and the reference standard were assessed. Interobserver agreement among the four radiologists was analyzed. Results: DL successfully segmented the myocardium in 99.3% of slices in the native T1 map and 89.8% of slices in the post-T1 map with Dice similarity coefficients of 0.86 ± 0.05 and 0.74 ± 0.17, respectively. Native T1 and ECV showed strong correlation and agreement between DL and the reference: for T1, r = 0.967 (95% confidence interval [CI], 0.951-0.978) and bias of 9.5 msec (95% limits of agreement [LOA], -23.6-42.6 msec); for ECV, r = 0.987 (95% CI, 0.980-0.991) and bias of 0.7% (95% LOA, -2.8%-4.2%) on per-subject basis. Agreements between DL and each of the four radiologists were excellent (intraclass correlation coefficient [ICC] of 0.98-0.99 for both native T1 and ECV), comparable to the pairwise agreement between the radiologists (ICC of 0.97-1.00 and 0.99-1.00 for native T1 and ECV, respectively). Conclusion: The DL algorithm allowed automated T1 and ECV measurements comparable to those of radiologists.
Journal of the Korean Society for information Management
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v.41
no.2
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pp.97-130
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2024
The current debate in the academic community is on the criteria for predatory journals. Researchers are perplexed about what constitutes a predatory journal. The purpose of this study is to investigate how South Korean researchers discover and evaluate predatory journals. In order to achieve this, we collected 2,484 statements, comprising posts and comments, from Korean researcher communities, namely the Biological Research Information Center (BRIC), Hibrain.net, Phdkim.net, and the Scholarly Ecosystem Against Fake Publication Environment (SAFE). We divided the data into three primary categories-journals, publishers, and researchers-for the topic analysis. For each statement, we assigned 11 in-depth subtopic tags based on these categories. Six main points of contention emerged from the combinations of these sub-topic tags: (1) researchers' confusion about predatory journals and discussions about research performance; (2)(3) researchers' positive and negative perceptions of predatory journals; (4) researchers' evaluation criteria for journal quality and problems associated with the quality of Korean journals; (5) changes in publishing brought about by the introduction of open access (OA) and associated issues; and (6) discussions on broader issues within the academic ecosystem. By using a qualitative approach to examine how South Korean researchers view predatory journals, this study aims to advance basic knowledge of the discourse around them in the communities of domestic researchers.
Jae-young Park;Jung Hwan Lee;Mo-Yeol Kang;Tae-Won Jang;Hyoung-Ryoul Kim;Se-Yeong Kim;Jongin Lee
Annals of Occupational and Environmental Medicine
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v.35
/
pp.24.1-24.15
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2023
Background: The construction workers are vulnerable to fatigue due to high physical workload. This study aimed to investigate the relationship between overwork and heart rate in construction workers and propose a scheme to prevent overwork in advance. Methods: We measured the heart rates of construction workers at a construction site of a residential and commercial complex in Seoul from August to October 2021 and develop an index that monitors overwork in real-time. A total of 66 Korean workers participated in the study, wearing real-time heart rate monitoring equipment. The relative heart rate (RHR) was calculated using the minimum and maximum heart rates, and the maximum acceptable working time (MAWT) was estimated using RHR to calculate the workload. The overwork index (OI) was defined as the cumulative workload evaluated with the MAWT. An appropriate scenario line (PSL) was set as an index that can be compared to the OI to evaluate the degree of overwork in real-time. The excess overwork index (EOI) was evaluated in real-time during work performance using the difference between the OI and the PSL. The EOI value was used to perform receiver operating characteristic (ROC) curve analysis to find the optimal cut-off value for classification of overwork state. Results: Of the 60 participants analyzed, 28 (46.7%) were classified as the overwork group based on their RHR. ROC curve analysis showed that the EOI was a good predictor of overwork, with an area under the curve of 0.824. The optimal cut-off values ranged from 21.8% to 24.0% depending on the method used to determine the cut-off point. Conclusion: The EOI showed promising results as a predictive tool to assess overwork in real-time using heart rate monitoring and calculation through MAWT. Further research is needed to assess physical workload accurately and determine cut-off values across industries.
The Journal of the Convergence on Culture Technology
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v.10
no.2
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pp.187-199
/
2024
Due to the educational ecosystem in South Korea, there is a significant need to explore a new balance for students who pursue sports rehabilitation education based on their academic performance, in order to help them adapt to their majors, find career paths, and foster motivation for employment. There is a lack of related research in this crucial phase. The purpose of this study is to ascertain the impact of sports rehabilitation education on career aspirations and employment motivation through psychological reactions. The research methodology involved conducting an online survey from December 11th to December 28th, 2023, targeting university students undergoing sports rehabilitation education, with a final collection of 212 survey responses used for analysis. The research findings indicate: firstly, that the knowledge of sports rehabilitation educators has a positive influence on voluntary psychology. Secondly, the competence of sports rehabilitation educators has a positive impact on voluntary psychology. Thirdly, the attitude of sports rehabilitation educators negatively affects involuntary psychology. Fourthly, voluntary psychology positively influences career aspirations. Finally, voluntary psychology positively influences employment motivation, while conversely, involuntary psychology negatively affects employment motivation. These research results are expected to contribute to the development of sports rehabilitation education that influences career paths and employment motivation through psychological reactions.
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