• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.1
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• pp.520-530
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• 2021

Objectives: This study aimed to identify the effects of music therapy on cognitive function, agitation, anxiety and depression in the elderly with dementia. Method: A comprehensive literature search was performed on PubMed, EMBASE, Cochrane Library, CINAHL, Web of Science, Google scholar and PsycINFO, for the period 2010 to 2019. In the meta-analysis, the standardized mean difference (Hedges' g) and 95% confidence interval were calculated as summary measure, and the random effect model and inverse variance method were applied using the RevMan 5.4 program. A total of 13 studies were included; all were determined to be acceptable, based on the Cochrane collaboration's tool for assessing risk of bias. Results: The effect size (Hedges' g) was 0.31 (95% CI: -0.02, 0.65) for cognition and -0.03 (95% CI: -0.17, 0.11) for agitation behavior as the primary outcomes, and 0.61 (95% CI: -1.17, -0.05) for anxiety and -0.44(95% CI: -0.88, 0.00) for depression as the secondary outcomes. Subgroup analysis by type of music intervention revealed that combined music therapy has a significantly increasing beneficial effect on cognition of dementia patients (g=0.45[95% CI: 0.03, 0.87]). Conclusion: Music therapy was determined to exert beneficial effects in reducing anxiety and depression, and combined music therapy demonstrated improved cognitive functions in elderly patients with dementia.

• Journal of The Korean Society of Integrative Medicine
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• v.9 no.3
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• pp.87-97
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• 2021

Purpose : The purpose of this meta-analysis was to evaluate the effects of transcranial direct current stimulation on the lower extremity function of stroke patients. Methods : Domestic data were gathered from studies that conducted clinical trials associated with transcranial direct current stimulation and its impact on lower extremity function of stroke patients. A total of 592 studies published between 2012 and 2020 were identified, with 7 studies satisfying the inclusion data. The studies consisted of patient, intervention, comparison, and outcome (PICO) data. The search outcomes were items associated with muscle activity, balance, muscle strength and walking ability. Cochrane risk of bias (ROB) was used to evaluate the quality of 3 randomized control trials. The quality of 4 non-randomized control trials was evaluated using risk of bias assessment tool for non-randomized studies (RoBANS). Effect sizes in this study were computed as the corrected standard mean difference (SMD). A random-effect model was used to analyze the effect size because of the high heterogeneity among the studies. Egger's regression and 'trim-and-fill' tests were carried out to analyze the publishing bias. Results : The following factors had a large total effect size (Hedges's g=2.10, 95 %CI=1.54~2.66) involving transcranial direct current stimulation on stroke patients: muscle activity (Hedges's g=2.38, 95 %CI=1.08~3.68), balance (Hedges's g4=2.41, 95 %CI=1.33~3.60), walking ability (Hedges's g=1.54, 95 %CI=0.49~2.59), and muscle strength (Hedges's g=2.45, 95 % CI: 0.85~4.05). Egger's regression test showed that the publishing bias had statistically significant differences but 'trim-and-fill' test showed that there was still statistical difference. Conclusion : This study provides evidence for the effectiveness of transcranial direct current stimulation on the lower extremity in terms of muscle activity, balance, walking ability, and muscle strength in stroke patients. However, due to the low quality of studies and high heterogeneity factors, the results of our study should be interpreted cautiously.

• Journal of Internet Computing and Services
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• v.23 no.3
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• pp.35-45
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• 2022

Even in recent years, treatment of first-aid patients is still often delayed due to a shortage of medical resources in marginalized areas. Research on automating the analysis of medical data to solve the problems of inaccessibility for medical services and shortage of medical personnel is ongoing. Computer vision-based medical inspection automation requires a lot of cost in data collection and labeling for training purposes. These problems stand out in the works of classifying lesion that are rare, or pathological features and pathogenesis that are difficult to clearly define visually. Anomaly detection is attracting as a method that can significantly reduce the cost of data collection by adopting an unsupervised learning strategy. In this paper, we propose methods for detecting abnormal images on chest X-RAY images as follows based on existing anomaly detection techniques. (1) Normalize the brightness range of medical images resampled as optimal resolution. (2) Some feature vectors with high representative power are selected in set of patch features extracted as intermediate-level from lesion-free images. (3) Measure the difference from the feature vectors of lesion-free data selected based on the nearest neighbor search algorithm. The proposed system can simultaneously perform anomaly classification and localization for each image. In this paper, the anomaly detection performance of the proposed system for chest X-RAY images of PA projection is measured and presented by detailed conditions. We demonstrate effect of anomaly detection for medical images by showing 0.705 classification AUROC for random subset extracted from the PadChest dataset. The proposed system can be usefully used to improve the clinical diagnosis workflow of medical institutions, and can effectively support early diagnosis in medically poor area.

• Safety and Health at Work
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• v.13 no.3
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• pp.263-268
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• 2022

Health care workers (HCWs) are more than ten times more likely to be infected with coronavirus infectious disease 2019 (COVID-19) than the general population, thus demonstrating the burden of COVID-19 among HCWs. Factors that expose HCWs to a differentially high-risk of COVID-19 acquisition are important to elucidate, enable appropriate public health interventions to mitigate against high risk and reduce adverse outcomes from the infection. We conducted a systematic review and meta-analysis to summarize and critically analyze the existing evidence on SARS-CoV-2 risk factors among HCWs. With no geographical limitation, we included studies, in any country, that reported (i) the PCR laboratory diagnosis of COVID-19 as an independent variable (ii) one or more COVID-19 risk factors among HCWs with risk estimates (relative risk, odds ratio, or hazard ratio) (iii) original, quantitative study design, and published in English or Mandarian. Our initial search resulted in 470 articles overall, however, only 10 studies met the inclusion criteria for this review. Out of the 10 studies included in the review, inadequate/lack of protective personal equipment, performing tracheal intubation, and gender were the most common risk factors of COVID-19. Based on the random effects adjusted pooled relative risk, HCWs who reported the use of protective personal equipment were 29% (95% CI: 16% to 41%) less likely to test positive for COVID-19. The study also revealed that HCWs who performed tracheal intubations were 34% (95% CI: 14% to 57%) more likely to test positive for COVID-19. Interestingly, this study showed that female HCWs are at 11% higher risk (RR 1.11 95% CI 1.01-1.21) of COVID-19 than their male counterparts. This article presents initial findings from a living systematic review and meta-analysis, therefore, did not yield many studies; however, it revealed a significant insight into better understanding COVID-19 risk factors among HCWs; insights important for devising preventive strategies that protect them from this infection.

• Journal of Intelligence and Information Systems
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• v.28 no.4
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• pp.347-364
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• 2022

Fraudulent companies or sellers strategically manipulate reviews to influence customers' purchase decisions; therefore, the reliability of reviews has become crucial for customer decision-making. Since customers increasingly rely on online reviews to search for more detailed information about products or services before purchasing, many researchers focus on detecting manipulated reviews. However, the main problem in detecting manipulated reviews is the difficulties with obtaining data with manipulated reviews to utilize machine learning techniques with sufficient data. Also, the number of manipulated reviews is insufficient compared with the number of non-manipulated reviews, so the class imbalance problem occurs. The class with fewer examples is under-represented and can hamper a model's accuracy, so machine learning methods suffer from the class imbalance problem and solving the class imbalance problem is important to build an accurate model for detecting manipulated reviews. Thus, we propose an OpenAI-based reviews generation model to solve the manipulated reviews imbalance problem, thereby enhancing the accuracy of manipulated reviews detection. In this research, we applied the novel autoregressive language model - GPT-3 to generate reviews based on manipulated reviews. Moreover, we found that applying GPT-3 model for oversampling manipulated reviews can recover a satisfactory portion of performance losses and shows better performance in classification (logit, decision tree, neural networks) than traditional oversampling models such as random oversampling and SMOTE.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.1
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• pp.276-290
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• 2023

Several efforts in Korea are currently underway with the goal of commercializing autonomous vehicles. Hence, various studies are emerging on autonomous vehicles that drive safely and quickly according to operating guidelines. The current study examines the path search of an autonomous vehicle from a microscopic viewpoint and tries to prove the efficiency required by learning the lane change of an autonomous vehicle through Deep Q-Learning. A SUMO was used to achieve this purpose. The scenario was set to start with a random lane at the starting point and make a right turn through a lane change to the third lane at the destination. As a result of the study, the analysis was divided into simulation-based lane change and simulation-based lane change applied with Deep Q-Learning. The average traffic speed was improved by about 40% in the case of simulation with Deep Q-Learning applied, compared to the case without application, and the average waiting time was reduced by about 2 seconds and the average queue length by about 2.3 vehicles.

• Safety and Health at Work
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• v.14 no.2
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• pp.141-152
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• 2023

Objective: We performed a meta-analysis of epidemiological results for the association between occupational exposure as a firefighter and cancer as part of the broader evidence synthesis work of the IARC Monographs program. Methods: A systematic literature search was conducted to identify cohort studies of firefighters followed for cancer incidence and mortality. Studies were evaluated for the influence of key biases on results. Random-effects meta-analysis models were used to estimate the association between ever-employment and duration of employment as a firefighter and risk of 12 selected cancers. The impact of bias was explored in sensitivity analyses. Results: Among the 16 included cancer incidence studies, the estimated meta-rate ratio, 95% confidence interval (CI), and heterogeneity statistic (I²) for ever-employment as a career firefighter compared mostly to general populations were 1.58 (1.14-2.20, 8%) for mesothelioma, 1.16 (1.08-1.26, 0%) for bladder cancer, 1.21 (1.12-1.32, 81%) for prostate cancer, 1.37 (1.03-1.82, 56%) for testicular cancer, 1.19 (1.07-1.32, 37%) for colon cancer, 1.36 (1.15-1.62, 83%) for melanoma, 1.12 (1.01-1.25, 0%) for non-Hodgkin lymphoma, 1.28 (1.02-1.61, 40%) for thyroid cancer, and 1.09 (0.92-1.29, 55%) for kidney cancer. Ever-employment as a firefighter was not positively associated with lung, nervous system, or stomach cancer. Results for mesothelioma and bladder cancer exhibited low heterogeneity and were largely robust across sensitivity analyses. Conclusions: There is epidemiological evidence to support a causal relationship between occupational exposure as a firefighter and certain cancers. Challenges persist in the body of evidence related to the quality of exposure assessment, confounding, and medical surveillance bias.

• Korean Journal of Social Welfare Studies
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• v.41 no.1
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• pp.175-201
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• 2010

The purpose of this study was to examine the mechanism through which youth school-based mentoring program impacts mentees' psychological and school-related outcomes such as self-esteem, self-efficacy, and attitudes toward school. The hypothetical model was assumed that mentors could improve their mentees' developmental outcomes through positive relationships with mentors as good role models and enhancement of help-seeking orientation. To investigate the mediating effect of process-related outcomes, structural equation modeling was used. The 97 adolescents were recruited through referral and random selection from middle schools in Seoul. The result showed that the effects of program participation were mediated by proximal changes in connectedness to role models and development of help-seeking orientation that, in turn, led to facilitate more positive attitudes toward school and academic activity, and improve psychological outcomes. Practice and policy implications as well as further research topics were discussed to aid the search for highly effective mentoring programs.

• Korean Journal of Radiology
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• v.22 no.12
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• pp.2082-2093
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• 2021

Objective: We conducted a systematic review and meta-analysis of the tissue adequacy and complication rates of percutaneous transthoracic needle biopsy (PTNB) for molecular analysis in patients with non-small cell lung cancer (NSCLC). Materials and Methods: We performed a literature search of the OVID-MEDLINE and Embase databases to identify original studies on the tissue adequacy and complication rates of PTNB for molecular analysis in patients with NSCLC published between January 2005 and January 2020. Inverse variance and random-effects models were used to evaluate and acquire meta-analytic estimates of the outcomes. To explore heterogeneity across the studies, univariable and multivariable metaregression analyses were performed. Results: A total of 21 studies with 2232 biopsies (initial biopsy, 8 studies; rebiopsy after therapy, 13 studies) were included. The pooled rates of tissue adequacy and complications were 89.3% (95% confidence interval [CI]: 85.6%-92.6%; I² = 0.81) and 17.3% (95% CI: 12.1%-23.1%; I² = 0.89), respectively. These rates were 93.5% and 22.2% for the initial biopsies and 86.2% and 16.8% for the rebiopsies, respectively. Severe complications, including pneumothorax requiring chest tube placement and massive hemoptysis, occurred in 0.7% of the cases (95% CI: 0%-2.2%; I² = 0.67). Multivariable meta-regression analysis showed that the tissue adequacy rate was not significantly lower in studies on rebiopsies (p = 0.058). The complication rate was significantly higher in studies that preferentially included older adults (p = 0.001). Conclusion: PTNB demonstrated an average tissue adequacy rate of 89.3% for molecular analysis in patients with NSCLC, with a complication rate of 17.3%. PTNB is a generally safe and effective diagnostic procedure for obtaining tissue samples for molecular analysis in NSCLC. Rebiopsy may be performed actively with an acceptable risk of complications if clinically required.

• Korean Journal of Radiology
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• v.22 no.10
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• pp.1680-1689
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• 2021

Objective: To investigate the diagnostic yield of diffusion-weighted imaging (DWI) in patients with transient global amnesia (TGA) and identify significant parameters affecting diagnostic yield. Materials and Methods: A systematic literature search of the MEDLINE and EMBASE databases was conducted to identify studies that assessed the diagnostic yield of DWI in patients with TGA. The pooled diagnostic yield of DWI in patients with TGA was calculated using the DerSimonian-Laird random-effects model. Subgroup analyses were also performed of slice thickness, magnetic field strength, and interval between symptom onset and DWI. Results: Twenty-two original articles (1732 patients) were included. The pooled incidence of right, left, and bilateral hippocampal lesions was 37% (95% confidence interval [CI], 30-44%), 42% (95% CI, 39-46%), and 25% (95% CI, 20-30%) of all lesions, respectively. The pooled diagnostic yield of DWI in patients with TGA was 39% (95% CI, 27-52%). The Higgins I² statistic showed significant heterogeneity (I² = 95%). DWI with a slice thickness ≤ 3 mm showed a higher diagnostic yield than DWI with a slice thickness > 3 mm (pooled diagnostic yield: 63% [95% CI, 53-72%] vs. 26% [95% CI, 16-40%], p < 0.01). DWI performed at an interval between 24 and 96 hours after symptom onset showed a higher diagnostic yield (68% [95% CI, 57-78%], p < 0.01) than DWI performed within 24 hours (16% [95% CI, 7-34%]) or later than 96 hours (15% [95% CI, 8-26%]). There was no difference in the diagnostic yield between DWI performed using 3T vs. 1.5T (pooled diagnostic yield, 31% [95% CI, 25-38%] vs. 24% [95% CI, 14-37%], p = 0.31). Conclusion: The pooled diagnostic yield of DWI in TGA patients was 39%. DWI obtained with a slice thickness ≤ 3 mm or an interval between symptom onset and DWI of > 24 to 96 hours could increase the diagnostic yield.