• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.32 no.1
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• pp.21-30
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• 2022

Objectives: The purpose of this study is to suggest an optimal method by comparing the analysis methods of work environment measurement datasets including left-censored data where one or more measurements are below the limit of detection (LOD). Methods: A computer program was used to generate left-censored datasets for various combinations of censoring rate (1% to 90%) and sample size (30 to 300). For the analysis of the censored data, the simple substitution method (LOD/2), β-substitution method, maximum likelihood estimation (MLE) method, Bayesian method, and regression on order statistics (ROS)were all compared. Each method was used to estimate four parameters of the log-normal distribution: (1) geometric mean (GM), (2) geometric standard deviation (GSD), (3) 95th percentile (X95), and (4) arithmetic mean (AM) for the censored dataset. The performance of each method was evaluated using relative bias and relative root mean squared error (rMSE). Results: In the case of the largest sample size (n=300), when the censoring rate was less than 40%, the relative bias and rMSE were small for all five methods. When the censoring rate was large (70%, 90%), the simple substitution method was inappropriate because the relative bias was the largest, regardless of the sample size. When the sample size was small and the censoring rate was large, the Bayesian method, the β-substitution method, and the MLE method showed the smallest relative bias. Conclusions: The accuracy and precision of all methods tended to increase as the sample size was larger and the censoring rate was smaller. The simple substitution method was inappropriate when the censoring rate was high, and the β-substitution method, MLE method, and Bayesian method can be widely applied.

• Journal of Korea Entertainment Industry Association
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• v.14 no.3
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• pp.431-442
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• 2020

This study examined the effect of the theratainment swiss ball exercise on the upper limb function, pain, and daily activities of a patient with axillary nerve injury. The research duration was from November 5^th, 2019 to February 25^th, 2020. The research subject was a 23-year-old female patient living in the metropolitan city of G in South Korea, and the A-B-A' type of single-subject experimental research design was used. In this study, repeated training was provided to the patient in the form of exercises employing different directions and gradually increased weights. The training increased the structural stability and mobility of the shoulder and was effective for pain relief as it strengthened shoulder function. The training helped the subject improve her posture change adaptability and reaction ability in different environments and ultimately enabled her to increase and maximize her performance of independent daily activities. This study thus demonstrated the positive effect of the Swiss ball exercise on the upper limb function, pain and disability, daily activities of a patient with axillary nerve injury and confirmed the potential of the exercise as an intervention method. Continued investigation to develop and test the effect of the Swiss ball exercise will be required for it to be used professionally as a therapeutic approach by occupational therapists in treating a variety of patients.

• Therapeutic Science for Rehabilitation
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• v.11 no.4
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• pp.85-97
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• 2022

Purpose : This study aimed to investigate the effects of a digital pegboard training program with visual and auditory feedback on hand function and visual perception in stroke patients. Methods : Twenty two participants were randomly assigned to an experimental or control group. The experimental group received training using a digital pegboard training program with visual and auditory feedback (n=11), while traditional occupational therapy was administered to the control group (n=11). Hand function was assessed before and after the intervention using the Nine-Hole Peg Test and manual function test (MFT), while visual perception was assessed using the Motor-Free Visual Perception Test-3rd edition (MVPT-3). Results : Following the intervention, both the experimental and control groups showed significant improvements in performance in the Nine-Hole Peg Test and MVPT-3 (p<.05). The improvement on both tests was significantly greater in the experimental group than in the control group (p<.05). Conclusion : The results suggest that digital pegboard training with visual and auditory feedback may improve hand function and visual perception in stroke patients. Therefore, this intervention can be effective in occupational therapy to aid the recovery of stroke patients.

• Journal of the Korean Society of Radiology
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• v.16 no.4
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• pp.405-410
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• 2022

In brachytherapy, a radiation source is inserted into the body to kill tumor tissue. Therefore, it is important to accurately measure the location of the source and the dose distribution. In this study, a dosimeter that can be used for brachytherapy was developed using CsPbBr₃ which is cheaper than the existing detector materials and has a simpler manufacturing process. The CsPbBr₃ dosimeter performance was evaluated by analyzing reproducibility, linearity, and distance dependence in ¹⁹²Ir source. As a result of reproducibility evaluation, the RSD was 1.36%, which satisfies the standard value of 1.5%. As a result of the linearity evaluation, the R² value was 0.9993, which satisfies the standard R² of 0.9990. The distance dependence evaluation showed a signal value that decreased exponentially as the distance increased. The evaluation results show that the CsPbBr₃ dosimeter satisfies the evaluation criteria and can be used as a brachytherapy quality assurance dosimeter.

• Therapeutic Science for Rehabilitation
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• v.11 no.3
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• pp.7-22
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• 2022

Objectives : This study was a systematic review of tongue movements in stroke patients with dysphagia. This study aimed to provide a basis for verifying the effects of tongue movement and identifying the tendency of tongue movement. Methods : A systematic review was conducted using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses checklist and flow chart. PubMed, MEDLINE, CINAHL, RISS, and e-articles databases were searched. A total of six documents were investigated, and the PEDro scale was used to evaluate the quality of the papers. Results : Three intervention methods were included in the six papers analyzed. Regarding the type of tongue exercise, three TPRT (Tongue to Palate Resistance Trainings) and two TSAT (Tongue Strength and Accuracy Training) were mediated through the IOPI (Iowa Oral Performance Instrument), and only one study applied TSE (Tongue Stretching Exercise). The treatment effects for each intervention implemented in the literature were confirmed to be effective. However, generalizability of findings is difficult because of the small sample size. Further, no significant difference was found between the experimental and control groups. Conclusions : This study can help occupational therapists provide efficient swallowing rehabilitation treatment by applying tongue exercises to stroke patients with dysphagia. More research should be conducted to determine the effects of tongue exercise.

• Journal of the Society of Disaster Information
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• v.19 no.1
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• pp.44-59
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• 2023

Purpose: In the event of mass casualties, triage must be done promptly and accurately so that as many patients as possible can be recovered and returned to the battlefield. However, medical personnel have received many tasks with less manpower, and the battlefield for classifying patients is too complex and uncertain. Therefore, we studied an artificial intelligence model that can assist and replace medical personnel on the battlefield. Method: The triage model is presented using reinforcement learning, a field of artificial intelligence. The learning of the model is conducted to find a policy that allows as many patients as possible to be treated, taking into account the condition of randomly set patients and the medical capability of the military hospital. Result: Whether the reinforcement learning model progressed well was confirmed through statistical graphs such as cumulative reward values. In addition, it was confirmed through the number of survivors whether the triage of the learned model was accurate. As a result of comparing the performance with the rule-based model, the reinforcement learning model was able to rescue 10% more patients than the rule-based model. Conclusion: Through this study, it was found that the triage model using reinforcement learning can be used as an alternative to assisting and replacing triage decision-making of medical personnel in the case of mass casualties.

• Korean Journal of Clinical Laboratory Science
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• v.55 no.3
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• pp.203-212
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• 2023

Since the coronavirus disease-2019 (COVID-19) outbreak, it has been generally believed that a medical technologists (MTs) are supposed to perform polymerase chain reaction tests and next-generation sequencing (NGS) in the hospitals. However, many do not recognize that the duty of MT for clinical genetic testing has not been stated in the Medical Laws (72.5% for MT, N=200; 62.8% for students, N=123). In this regard, to evaluate the feasibility of MT's role for NGS genetic testing, we requested our subjects to fill out an online survey and analyzed the data. Among them, it shows that the scope of MT's role, including NGS performance should include clinical genetic testing (99.5% for MT, N=200; 86.8% for students, N=123). Also, questions on clinical genetics, which is associated with both cellular genetics and molecular genetic questions should be included in the National MT License Problem Bank (97.5% for MT; 71.4% for students). Based on these results, the Korean Association of Medical Technologists needs to cooperate synergically with the Academic Association of Biomedical Laboratory Science with respect to genetic education and legislation for the future benefit of both MTs and students.

• Phonetics and Speech Sciences
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• v.14 no.4
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• pp.45-56
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• 2022

This paper proposes an optimal methodology for automatically diagnosing and predicting the severity of the chronic kidney disease (CKD) using patients' utterances. In patients with CKD, the voice changes due to the weakening of respiratory and laryngeal muscles and vocal fold edema. Previous studies have phonetically analyzed the voices of patients with CKD, but no studies have been conducted to classify the voices of patients. In this paper, the utterances of patients with CKD were classified using the variety of utterance types (sustained vowel, sentence, general sentence), the feature sets [handcrafted features, extended Geneva Minimalistic Acoustic Parameter Set (eGeMAPS), CNN extracted features], and the classifiers (SVM, XGBoost). Total of 1,523 utterances which are 3 hours, 26 minutes, and 25 seconds long, are used. F1-score of 0.93 for automatically diagnosing a disease, 0.89 for a 3-classes problem, and 0.84 for a 5-classes problem were achieved. The highest performance was obtained when the combination of general sentence utterances, handcrafted feature set, and XGBoost was used. The result suggests that a general sentence utterance that can reflect all speakers' speech characteristics and an appropriate feature set extracted from there are adequate for the automatic classification of CKD patients' utterances.

• Journal of Digital Convergence
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• v.20 no.1
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• pp.203-211
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• 2022

This study is to examine the causes of research misconduct such as plagiarism, forgery, redundant publication, unfair author expression, and incapacitation of the research ethics system of university researchers and to suggest improvement plan. It basically relied on literature research. In order to supplement the deficiencies in literature research, I sought advice from an expert professor who had experience working in a research-related field in university or who is currently in a position related to research ethics through the delphi-method. As a result of the study, from the perspective of individual researchers, the complacent attitude, dishonesty, and greed for research funds were identified as the main reasons. In terms of organization, it was analyzed for reasons such as lack of detail and application of regulations, lack of verification system, and performance-oriented research environment. In order to overcome research misconduct caused by the researcher's personal reasons, regularization, increase in the number of research ethics education, and strengthening personal penalties were suggested. As a way to overcome irregularities arising from institutional reasons, the reinforcement of the verification system, the reinforcement of the whistle-blower's personal protection system, the omission of promotion, and the quality and quantitative balance of research evaluation was suggested.

• Journal of the Korean Society for information Management
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• v.39 no.1
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• pp.91-117
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• 2022

The number of depressed patients in Korea and around the world is rapidly increasing every year. However, most of the mentally ill patients are not aware that they are suffering from the disease, so adequate treatment is not being performed. If depressive symptoms are neglected, it can lead to suicide, anxiety, and other psychological problems. Therefore, early detection and treatment of depression are very important in improving mental health. To improve this problem, this study presented a deep learning-based depression tendency model using Korean social media text. After collecting data from Naver KonwledgeiN, Naver Blog, Hidoc, and Twitter, DSM-5 major depressive disorder diagnosis criteria were used to classify and annotate classes according to the number of depressive symptoms. Afterwards, TF-IDF analysis and simultaneous word analysis were performed to examine the characteristics of each class of the corpus constructed. In addition, word embedding, dictionary-based sentiment analysis, and LDA topic modeling were performed to generate a depression tendency classification model using various text features. Through this, the embedded text, sentiment score, and topic number for each document were calculated and used as text features. As a result, it was confirmed that the highest accuracy rate of 83.28% was achieved when the depression tendency was classified based on the KorBERT algorithm by combining both the emotional score and the topic of the document with the embedded text. This study establishes a classification model for Korean depression trends with improved performance using various text features, and detects potential depressive patients early among Korean online community users, enabling rapid treatment and prevention, thereby enabling the mental health of Korean society. It is significant in that it can help in promotion.