• 한국응급구조학회지
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• 제17권2호
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• pp.89-97
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• 2013

Purpose : The purpose of this study was to investigate the correlation between stress and maxillofacial injuries in male students. Methods : The subjects were 386 male students who were 18 years or more. Mean age was $20.99{\pm}2.80$ years. Data were collected using a self-reported questionnaire from March 7 to March 28, 2013. We surveyed maxillofacial injuries, mouth guards use and stress in male students majoring physical education. The data were analyzed by Cochran's Mantel-Haenszel, McNemar test and logistic multiple regression. Results : Those who had clenching habit and maxillofacial pain accounted for 48.7%. The pain was 3.23 folds higher in clenching habit than those who had not (OR=3.23, p <.001). The more stress they had, the more clenching habit (OR=2.13) and pain(OR=1.68) did they have. Within 2 years, those having maxillofacial injury accounted for 53.2% and 78.6% of them put on maxillofacial protection guard. In rule for mouth guard use, 39.9% had no maxillofacial injury. Maxillofacial injury was 2.41 folds higher in those who had no mouth guard usee (OR=2.41). Conclusion : Maxillofacial injury had a close correlation with mouth guard use and stress. Therefore, it is very important to establish the rule for mouth guard use in sports activities.

• Korean Journal of Radiology
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• 제20권5호
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• pp.812-822
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• 2019

Objective: To assess the diagnostic value of combining diffusion-weighted imaging (DWI) with conventional magnetic resonance imaging (MRI) for differentiating between pathologic and traumatic fractures at extremities from metastasis. Materials and Methods: Institutional Review Board approved this retrospective study and informed consent was waived. This study included 49 patients each with pathologic and traumatic fractures at extremities. The patients underwent conventional MRI combined with DWI. For qualitative analysis, two radiologists (R1 and R2) independently reviewed three imaging sets with a crossover design using a 5-point scale and a 3-scale confidence level: DWI plus non-enhanced MRI (NEMR; DW set), NEMR plus contrast-enhanced fat-saturated T1-weighted imaging (CEFST1; CE set), and DWI plus NEMR plus CEFST1 (combined set). McNemar's test was used to compare the diagnostic performances among three sets and perform subgroup analyses (single vs. multiple bone abnormality, absence/presence of extra-osseous mass, and bone enhancement at fracture margin). Results: Compared to the CE set, the combined set showed improved diagnostic accuracy (R1, 84.7 vs. 95.9%; R2, 91.8 vs. 95.9%, p < 0.05) and specificity (R1, 71.4% vs. 93.9%, p < 0.005; R2, 85.7% vs. 98%, p = 0.07), with no difference in sensitivities (p > 0.05). In cases of absent extra-osseous soft tissue mass and present fracture site enhancement, the combined set showed improved accuracy (R1, 82.9-84.4% vs. 95.6-96.3%, p < 0.05; R2, 90.2-91.1% vs. 95.1-95.6%, p < 0.05) and specificity (R1, 68.3-72.9% vs. 92.7-95.8%, p < 0.005; R2, 83.0-85.4% vs. 97.6-98.0%, p = 0.07). Conclusion: Combining DWI with conventional MRI improved the diagnostic accuracy and specificity while retaining sensitivity for differentiating between pathologic and traumatic fractures from metastasis at extremities.

• 경영정보학연구
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• 제16권3호
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• pp.161-177
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• 2014

기업신용등급은 금융시장의 신뢰를 구축하고 거래를 활성화하는데 있어 매우 중요한 요소로서, 오래 전부터 학계에서는 보다 정확한 기업신용등급 예측을 가능케 하는 다양한 모형들을 연구해 왔다. 구체적으로 다중판별분석(Multiple Discriminant Analysis, MDA)이나 다항 로지스틱 회귀분석(multinomial logistic regression analysis, MLOGIT)과 같은 통계기법을 비롯해, 인공신경망(Artificial Neural Networks, ANN), 사례기반추론(Case-based Reasoning, CBR), 그리고 다분류 문제해결을 위해 확장된 다분류 Support Vector Machines(Multiclass SVM)에 이르기까지 다양한 기법들이 학자들에 의해 적용되었는데, 최근의 연구결과들에 따르면 이 중에서도 다분류 SVM이 가장 우수한 예측성과를 보이고 있는 것으로 보고되고 있다. 본 연구에서는 이러한 다분류 SVM의 성능을 한 단계 더 개선하기 위한 대안으로 유전자 알고리즘(GA, Genetic Algorithm)을 활용한 최적화 모형을 제안한다. 구체적으로 본 연구의 제안모형은 유전자 알고리즘을 활용해 다분류 SVM에 적용되어야 할 최적의 커널 함수 파라미터값들과 최적의 입력변수 집합(feature subset)을 탐색하도록 설계되었다. 실제 데이터셋을 활용해 제안모형을 적용해 본 결과, MDA나 MLOGIT, CBR, ANN과 같은 기존 인공지능/데이터마이닝 기법들은 물론 지금까지 가장 우수한 예측성과를 보이는 것으로 알려져 있던 전통적인 다분류 SVM 보다도 제안모형이 더 우수한 예측성과를 보임을 확인할 수 있었다.