• Journal of Acupuncture Research
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• v.30 no.2
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• pp.9-15
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• 2013

Objectives : This study was done for reporting the effect of moxibustion therapy on Ryodoraku score of the patients with degenerative arthritis of knee joint. Methods : We investigated 65 cases of patients with degenerative arthritis of knee joint, and devided patients into two groups : One group treated by moxibustion therapy, which was not applied to the other group we analyzed of each group the Ryodoraku score(F1, F6) of each group before and after moxibustion therapy and compared it. Results : 1. In moxibustion therapy group compared with baseline, at final, Ryodoraku score(F1, F6) was significantly increased. 2. At final, moxibustion therapy group showed significant increase on Ryodoraku score(F1, F6) score compared with non moxibustion therapy group. Conclusions : It is suggested that Ryodoraku score(F1, F6) should be available for diagnosing degenerative arthritis of knee joint.

• The Journal of Pediatrics of Korean Medicine
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• v.30 no.3
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• pp.31-41
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• 2016

Objectives The purpose of this study is to investigate the characteristics of Ryodoraku Score in the children who visited department of pediatrics, hospital of Korean medicine with allergic rhinitis as the chief complaint. Methods Subjects were 80 children with allergic rhinitis. We calculated the average Ryodoraku Score (RS, ${\mu}A$), and compared the average of each meridian system. And we classified the children by several groups (depending on age, additional allergic disease), and accomplished a comparative analysis. Results 1. The average of Ryodoraku Score in 80 children was $76.36{\pm}22.72$. 2. The figure of H3 (心), H5 (三焦), F1 (脾), F2 (肝), F3 (腎), F4 (膀胱), F5 (三焦), F6 (胃) had significant statistical differences compared to the total average. 3. Comparing the group having only allergic rhinitis to group having allergic rhinitis and other allergic disease, showed significant statistical difference in H2 (心包), H3 (心). 4. Analyzed by age, there's a significant statistical difference in F1 (脾), F4 (膀胱). Conclusion We found that H5 (三焦), F1 (脾), F4 (膀胱) showed significant statistical difference in Ryodoraku Score, and F1 (脾) had the highest relevance. The research indicate meaningful difference depending on age, additional allergic disease.

• 한국어정보학회:학술대회논문집
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• 2016.10a
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• pp.321-323
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• 2016

최근 연구에서 기계학습 중 지도학습 방법으로 개체명 인식을 하고 있다. 그러나 지도 학습 방법은 데이터를 만드는 비용과 시간이 많이 필요로 한다. 본 연구에서는 주석 된 말뭉치를 사용하여 지도 학습 방법을 사용 한다. 의생명 개체명 인식은 Protein, RNA, DNA, Cell type, Cell line 등을 포함한 텍스트 처리에 중요한 기초 작업입니다. 그리고 의생명 지식 검색에서 가장 기본과 핵심 작업 중 하나이다. 본 연구에서는 순환형 신경망과 워드 임베딩을 자질로 사용한 조건적 임의 필드에 대한 성능을 비교한다. 조건적 임의 필드에 N_Gram만을 자질로 사용한 것을 기준점으로 설정 하였고, 기준점의 결과는 70.09% F1 Score이다. RNN의 jordan type은 60.75% F1 Score, elman type은 58.80% F1 Score의 성능을 보여준다. 조건적 임의 필드에 CCA, GLOVE, WORD2VEC을 사용 한 결과는 각각 72.73% F1 Score, 72.74% F1 Score, 72.82% F1 Score의 성능을 얻을 수 있다.

• Research in Community and Public Health Nursing
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• v.4 no.2
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• pp.131-138
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• 1993

The purpose of this study was to identify K.A.P. of industrial workers on health management. The study was conducted Dec 5, 1992 to March 10, 1993. The results were as follows : 1. The total Score of K.A.P. of industrial worker on the Knowledge of industrial health management was 2.52, the Attitude score was 42, the Practice score 2, 62. 2. The office workers' score on K.A.P.(T=-2. 11, P=.038) Attitude score(T=-2.03, P=.045) were higher than that of productive workers' 3. The K.A.P. score of married worker was higher than that of single workers, and showed significant differences statistically. 4. There are significant statistical differences in the Attitude score of workers according to age(F=2.26, F=.0304). 5. There were statistically significant differences among total Scores of K.A.P. (F=3.1141, P=.0498). Practice score(F=8.4421, P=.0004), Knowledge Score (F=3.5833, P=.0323). Performed 84.7%. 6. The relationship between industrial worker's health level score and industrial health status had reverse relationship(R=-.7689. P<.001) Therefore the companies that performed better health management attained a higher health level.

• Journal of Oriental Neuropsychiatry
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• v.20 no.4
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• pp.115-126
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• 2009

Objectives : This study was performed to investigate the relationship between decision making style and learning style according to Sasang constitution. Methods : The subjects were 213 nursing students of K college in Jeonbuk, and the period of data gathering was limited from 1 Sep. 2009 to 7 Sep. 2009. The instrument tools included QSCC II, decision making style, and learning style. The collected data were analyzed by SPSS-PC programme. Results : 1. Decision making style: Soeumin group had significantly high score in rational score compared with Soyangin(F=7.174 p=.001), and in dependent score compared with Taeumin and Soyangin (F=3.414, p=.035). 2. Learning style: Soyangin group had significantly high score in cooperation score compared with Taeumin(F=5.688 p=.004), and Taeumin group had significantly high score in emulous score compared with Soeumin and Soyangin (F=.148, p=.002). Conclusions : In conclusion, it was found that decision making style and learning style are significantly different according to Sasang constitution. Therefore, these results suggest that nursing educational program needs to be developed considering Sasang constitution.

• Journal of Acupuncture Research
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• v.29 no.3
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• pp.115-120
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• 2012

Objectives : This study was done for reporting the effect of acupuncture treatment on Ryodoraku score of the patients with chronic low back pain due to the kidney deficiency Methods : We investigated 37 cases of patients with chronic low back pain due to the kidney deficiency, and devided patients into two groups : We specially treated one group by acupuncture treatment, which was not applied to the other group we analyzed of each group the Ryodoraku score(F3) of each group before and after acupuncture treatment and compared it. Results : 1. In acupuncture treatment group compared with baseline, at final, Ryodoraku score(F3) was significantly increased. 2. At final, acupuncture treatment group showed significant increase on Ryodoraku score(F3) score compared with non acupuncture treatment group. Conclusions : It is suggested that Ryodoraku score(F3) should be available for diagnosing kidney deficiency-induced chronic low back pain as a promising diagnostic index and a outcome measurement.

• Journal of the Korea Convergence Society
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• v.13 no.2
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• pp.13-20
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• 2022

This study is to develop a named entity recognition model specialized in criminal investigation domains using deep learning techniques. Through this study, we propose a system that can contribute to analysis of crime for prevention and investigation using data analysis techniques in the future by automatically extracting and categorizing crime-related information from text-based data such as criminal judgments and investigation documents. For this study, the criminal investigation domain text was collected and the required entity name was newly defined from the perspective of criminal analysis. In addition, the proposed model applying KoELECTRA, a pre-trained language model that has recently shown high performance in natural language processing, shows performance of micro average(referred to as micro avg) F1-score 98% and macro average(referred to as macro avg) F1-score 95% in 9 main categories of crime domain NER experiment data, and micro avg F1-score 98% and macro avg F1-score 62% in 56 sub categories. The proposed model is analyzed from the perspective of future improvement and utilization.

• Journal of Integrative Natural Science
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• v.11 no.3
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• pp.161-164
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• 2018

Over the past decade, mass spectrometry-based metabolomics, especially two dimensional gas chromatography mass spectrometry (GCxGC/TOF-MS), has become a key analytical tool for metabolomics data because of its sensitivity and ability to analyze complex biological or biochemical sample. However, the need to reduce variations within/between experiments has been reported and methodological developments to overcome such problem has long been a critical issue. Along with methodological developments, developing reasonable performance measure has also been studied. Following four numerical measures have been typically used for comparison: sensitivity, specificity, receiver operating characteristic (ROC) curves, and positive predictive value (PPV). However, more recently, such measures are replaced with F1 score in many fields including metabolomics area without any carefulness of its validity. Thus, we want to investigate the validity of F1 score on two examples, with the goal of raising the awareness in choosing appropriate performance comparison measure. We noticed that F1 score itself, as a performance measure, was not good enough. Accordingly, we suggest that F1 score be supplemented with other performance measure such as specificity to improve its validity.

• Annual Conference on Human and Language Technology
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• 2016.10a
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• pp.321-323
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• 2016

최근 연구에서 기계학습 중 지도학습 방법으로 개체명 인식을 하고 있다. 그러나 지도 학습 방법은 데이터를 만드는 비용과 시간이 많이 필요로 한다. 본 연구에서는 주석 된 말뭉치를 사용하여 지도 학습 방법을 사용 한다. 의생명 개체명 인식은 Protein, RNA, DNA, Cell type, Cell line 등을 포함한 텍스트 처리에 중요한 기초 작업입니다. 그리고 의생명 지식 검색에서 가장 기본과 핵심 작업 중 하나이다. 본 연구에서는 순환형 신경망과 워드 임베딩을 자질로 사용한 조건적 임의 필드에 대한 성능을 비교한다. 조건적 임의 필드에 N_Gram만을 자질로 사용한 것을 기준점으로 설정 하였고, 기준점의 결과는 70.09% F1 Score이다. RNN의 jordan type은 60.75% F1 Score, elman type은 58.80% F1 Score의 성능을 보여준다. 조건적 임의 필드에 CCA, GLOVE, WORD2VEC을 사용 한 결과는 각각 72.73% F1 Score, 72.74% F1 Score, 72.82% F1 Score의 성능을 얻을 수 있다.

• Journal of Radiation Industry
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• v.18 no.3
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• pp.177-182
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• 2024

The purpose of this study is to develop a CNN based deep learning model that can effectively detect pneumonia by analyzing chest X-ray images of adults over the age of 20 and compare it with VUNO, LUNIT a commercialized AI model. The data of chest X-ray image was evaluate based on accuracy, precision, recall, F1 score, and AUC score. The CNN model recored an accuracy of 82%, precision 76%, recall 99%, F1 score 86%, and AUC score 0.7937. The VUNO model recordded an accuracy of 84%, precision 81%, recall 94%, F1 score 87%, and AUC score 0.8233. The LUNIT model recorded an accuracy of 77%, precision 72%, recall 96%, F1 score 83%, and AUC score 0.7436. As a result of the Confusion Matrix analysis, the CNN model showe FN (3), showing the highest recall rate (99%) in the diagnosis of pneumonia. The VUNO model showed excellent overall perfomance with high accuracy (84%) and AUC score (0.8233), and the LUNIT model showed high recall rate (96%) but the accuracy and precision showed relatively low results. This study will be able to provide basic data useful for the development of a pneumonia diagnosis system by comprehensively considers the perfomance of the medel is necessary to effectively discriminate between penumonia and normal groups.