• 한국도로학회논문집
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• 제20권3호
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• pp.27-37
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• 2018

PURPOSES : The objective of this study is to develop a pavement rehabilitation decision tree considering current pavement condition by evaluating severity and distress types such as roughness, cracking and rutting. METHODS : To improve the proposed overall rehabilitation decision tree, current decision tree from Korea and decision trees from other countries were summarized and investigated. The problem when applying the current rehabilitation method obtained from the decision tree applied in Seoul was further analyzed. It was found that the current decision trees do not consider different distress characteristics such as crack type, road types and functions. Because of this, different distress values for IRI, crack rate and plastic deformation was added to the proposed decision tree to properly recommend appropriate pavement rehabilitation. Utilizing the 2017 Seoul pavement management system data and considering all factors as discussed, the proposed overall decision tree was revised and improved. RESULTS :In this study, the type of crack was included to the decision tree. Meanwhile current design thickness and special asphalt mixture were studied and improved to be applied on different pavement condition. In addition, the improved decision tree was incorporated with the Seoul asphalt overlay design program. In the case of Seoul's rehabilitation budget, rehabilitation budget can be optimized if a 25mm milling and overlay thickness is used. CONCLUSIONS:A practical and theoretical evaluation tool in pavement rehabilitation design was presented and proposed for Seoul City.

• Physical Therapy Rehabilitation Science
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• 제11권3호
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• pp.285-295
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• 2022

Objective: The purpose of this study is to use logistic regression and decision tree analysis to identify the factors that affect the success or failurein the national physical therapy examination; and to build and compare predictive models. Design: Secondary data analysis study Methods: We analyzed 76,727 subjects from the physical therapy national examination data provided by the Korea Health Personnel Licensing Examination Institute. The target variable was pass or fail, and the input variables were gender, age, graduation status, and examination area. Frequency analysis, chi-square test, binary logistic regression, and decision tree analysis were performed on the data. Results: In the logistic regression analysis, subjects in their 20s (Odds ratio, OR=1, reference), expected to graduate (OR=13.616, p<0.001) and from the examination area of Jeju-do (OR=3.135, p<0.001), had a high probability of passing. In the decision tree, the predictive factors for passing result had the greatest influence in the order of graduation status (x²=12366.843, p<0.001) and examination area (x²=312.446, p<0.001). Logistic regression analysis showed a specificity of 39.6% and sensitivity of 95.5%; while decision tree analysis showed a specificity of 45.8% and sensitivity of 94.7%. In classification accuracy, logistic regression and decision tree analysis showed 87.6% and 88.0% prediction, respectively. Conclusions: Both logistic regression and decision tree analysis were adequate to explain the predictive model. Additionally, whether actual test takers passed the national physical therapy examination could be determined, by applying the constructed prediction model and prediction rate.

• Physical Therapy Rehabilitation Science
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• 제12권2호
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• pp.80-91
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• 2023

Objective: The purpose of this study is to identify factors that affect the incidence of hypertension using logistic regression and decision tree analysis, and to build and compare predictive models. Design: Secondary data analysis study Methods: We analyzed 9,859 subjects from the Korean health panel annual 2019 data provided by the Korea Institute for Health and Social Affairs and National Health Insurance Service. Frequency analysis, chi-square test, binary logistic regression, and decision tree analysis were performed on the data. Results: In logistic regression analysis, those who were 60 years of age or older (Odds ratio, OR=68.801, p<0.001), those who were divorced/widowhood/separated (OR=1.377, p<0.001), those who graduated from middle school or younger (OR=1, reference), those who did not walk at all (OR=1, reference), those who were obese (OR=5.109, p<0.001), and those who had poor subjective health status (OR=2.163, p<0.001) were more likely to develop hypertension. In the decision tree, those over 60 years of age, overweight or obese, and those who graduated from middle school or younger had the highest probability of developing hypertension at 83.3%. Logistic regression analysis showed a specificity of 85.3% and sensitivity of 47.9%; while decision tree analysis showed a specificity of 81.9% and sensitivity of 52.9%. In classification accuracy, logistic regression and decision tree analysis showed 73.6% and 72.6% prediction, respectively. Conclusions: Both logistic regression and decision tree analysis were adequate to explain the predictive model. It is thought that both analysis methods can be used as useful data for constructing a predictive model for hypertension.

• 한국한의학연구원논문집
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• 제17권2호
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• pp.121-127
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• 2011

Objectives : In the clinical field, it is important to understand the factors that have effects on a certain disease or symptom. For this, many researchers apply Data Mining method to the clinical data that they have collected. One of the efficient methods for Data Mining is decision tree induction. Many researchers have studied to find the best split criteria of decision tree; however, various split criteria coexist. Methods : In this paper, we applied several split criteria(Information Gain, Gini Index, Chi-Square) to Sasang constitutional clinical information and compared each decision tree in order to find optimal split criteria. Results & Conclusion : We found BMI and body measurement factors are important factors to Sasang constitution by analyzing produced decision trees with different split measures. And the decision tree using information gain had the highest accuracy. However, the decision tree that produced highest accuracy is changed depending on given data. So, researcher have to try to find proper split criteria for given data by understanding attribute of the given data.

• 한국도로학회논문집
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• 제11권2호
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• pp.37-44
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• 2009

현재 국도 PMS(Favement Management System)에서 적용하고 있는 보수공법결정체계는 소성변형과 균열의 기준치값에 대한 설정 근거가 명확하지 않다. 본 연구에서는 일반국도에서 아스팔트 콘크리트 포장의 보수 시 보수공법결정기준에 대한 근거를 제시하기 위한 것이다. 이를 위해 전국 일반국도 아스팔트 포장 구간을 대표할 수 있는 대표 구간을 선정하고, 포장전문가 패널(panel)을 선정하여 선정된 구간을 대상으로 패널이 대표구간을 평가하여 보수공법을 제안하였다. 포장전문가 패널이 대표구간을 평가한 결과를 분석하여 다음과 같이 보수공법 결정 기준의 근거를 마련하였다. 균열의 경우 절삭 덧씌우기를 요구하는 균열율은 35%, 덧씌우기 이상의 기준으로서 균열율 20%를 제안하였다. 소성변형의 경우 절삭 덧씌우기를 필요로 하는 소성변형 값은 13mm, 덧씌우기 이상을 요구하는 소성변형의 기준으로서 10mm를 사용할 것을 제안하였다.

• 전자공학회논문지CI
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• 제48권2호
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• pp.28-37
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• 2011

최근 건강에 대한 관심이 고조 되면서 발과 다리에 대한 진단, 치료, 예방의 전반적인 진료를 맡고 있는 족부의학(Podiatry)이 주목받고 있지만 국내 연구는 미비한 실정이다. 또한 임상 데이터 분석에 있어 대부분의 기존 연구들은 기초 통계적인 방법에 근거한 정량분석만을 수행함으로서, 획득된 정보를 임상에 적용 하는데 있어서는 충분한 신뢰성을 보장할 수 없다. 임상데이터 마이닝은 데이터마이닝의 다양한 분석 방법론을 이용하여 의료 현장에서 발생한 임상 데이터를 분석함으로서 전문가의 진단과 치료 과정의 결정에 도움을 주고 있다. 결정트리(Decision Tree) 알고리즘은 분석과정의 설명과 표현성이 좋고, 결과에 대한 해석이 편리하여 임상에서 적용하기가 용이하다. 본 연구에서는 신뢰성 있는 족부 임상 진단 평가를 위해 충남대학교병원 재활의학과 신발클리닉에 내원한 환자 1310명(남자:633명, 여자:677명)의 2620족(foot)을 대상으로 수집된 진료 데이터에 결정트리를 적용하여 22개의 족부 질환 인자에 따르는 15개의 족부 질환을 분류하고 그에 대한 64개의 진단 규칙을 탐사 하였다. 또한 5개의 클래스(영유아, 소아, 청소년, 노인, 전체)로 분류된 각 그룹들로부터 생성된 결정 트리를 통해 각 클래스의 질환 특징과 질환 주요 인자, 클래스 간 상관관계를 비교, 분석하였다. 탐사된 결과는 족부 임상 전문가의 의사결정에 더욱 정성적이고 유용한 선험적 지식을 제공할 것이고, 효과적이고 정확한 진단과 예측을 위한 임상 도구로써 사용될 수 있다.

• 대한한의학회지
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• 제33권4호
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• pp.1-8
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• 2012

Objectives: The purpose of this study was to specify major tongue diagnostic indicators and evaluate their significance in discriminating pattern identification subtypes in stroke patients. Methods: This study used a community based multi-center observational design. Participants (n=1,502) were stroke patients admitted to 11 oriental medical university hospitals between December 2006 and February 2010. To determine which tongue indicator affected each pattern identification, a decision tree analysis of the chi-square automatic interaction detector (CHAID) algorithm was performed. The chi-squared test was used as the criterion in splitting data with a p-value less than 0.05 for division, which is the main procedure for developing a decision tree. The minimum sample size for each node was specified as n =10, and branching was limited to two levels. Results: From the 9 tongue diagnostic indicators, 6 major tongue indicators (red tongue, pale tongue, yellow fur, white fur, thick fur, and teeth-marked tongue) were identified through the decision tree analysis. Furthermore, each pattern identification was composed of specific combinations of the 6 major tongue indicators. Conclusions: This study suggests that the 6 tongue indicators identified through the decision tree analysis can be used to discriminate pattern identification subtypes in stroke patients. However, it is still necessary to re-evaluate other pattern identification indicators to further the objectivity and reliability of traditional Korean medicine.

• 한국건설관리학회논문집
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• 제12권6호
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• pp.101-109
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• 2011

온실가스 배출로 인한 기후변화가 심각한 문제로 대두되면서, 국내 외에서 건물 에너지 절감을 위한 노력이 전개되고 있다. 특히, 국내 주거용 건축물 사용단계의 에너지 사용에 따른 온실가스 배출량은 전 생애주기에서 매우 큰 비중을 차지하고 있으며, 노후 공동주택의 수가 급격히 증가하고 있는 상황에서 기존 공동주택의 개선을 통한 에너지 절감의 중요성은 더욱 높아지고 있다. 그러나, 기존 공동주택의 개선에 대한 의사결정 과정에서, 에너지 절감에 대한 부분은 주요 고려사항으로 반영되지 못하고 있으며, 이를 반영하기 위해 필요한 의사결정 지원도구 역시 미비한 실정이다. 본 논문은 공동주택 개선여부의사결정 단계에서 활용할 수 있는 의사결정 지원 시스템을 개발하는 첫 단계로서, 유사 특성을 지닌 공동주택 단지간의 군집을 형성하는 분류체계를 구축하고자 했다. 이를 위해 데이터마이닝 기법 중 하나인 의사결정나무를 활용하여 공동주택 단지 특성 및 전력, 가스, 지역난방 에너지 사용량 기반의 군집을 형성했다. 향후 본 연구의 결과를 더욱 발전시켜 공동주택 개선단계에서의 의사결정 시 에너지 사용량을 고려사항으로 반영함으로써, 노후 공동주택 개선을 통한 에너지 절감 및 이산화탄소 배출량 감축 효과를 극대화할 수 있을 것으로 기대된다.

• 보건행정학회지
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• 제26권4호
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• pp.289-304
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• 2016

Background: Rehabilitations in subacute phase are different from acute treatments regarding the characteristics and required resource consumption of the treatments. Lack of accuracy and validity of the Korean Diagnosis Related Group and Korean Out-Patient Group for the acute patients as the case-mix and payment tool for rehabilitation inpatients have been problematic issues. The objective of the study was to develop the Korean Rehabilitation Patient Group (KRPG) reflecting the characteristics of rehabilitation inpatients. Methods: As a retrospective medical record survey regarding rehabilitation inpatients, 4,207 episodes were collected through 42 hospitals. Considering the opinions of clinical experts and the decision-tree analysis, the variables for the KRPG system demonstrating the characteristics of rehabilitation inpatients were derived, and the splitting standards of the relevant variables were also set. Using the derived variables, we have drawn the rehabilitation inpatient classification model reflecting the clinical situation of Korea. The performance evaluation was conducted on the KRPG system. Results: The KRPG was targeted at the inpatients with brain or spinal cord injury. The etiologic disease, functional status (cognitive function, activity of daily living, muscle strength, spasticity, level and grade of spinal cord injury), and the patient's age were the variables in the rehabilitation patients. The algorithm of KRPG system after applying the derived variables and total 204 rehabilitation patient groups were developed. The KRPG explained 11.8% of variance in charge for rehabilitation inpatients. It also explained 13.8% of variance in length of stay for them. Conclusion: The KRPG version 1.0 reflecting the clinical characteristics of rehabilitation inpatients was classified as 204 groups.

• 한국노년학
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• 제38권2호
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• pp.351-364
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• 2018

본 연구는 김포시 거주 노인들을 대상으로 노인복지관 이용 결정요인을 파악하는데 목적을 두고 있다. 그 이유는 노인복지관이 종합서비스 제공기관으로 국가정책 차원에 명시되어 있음에도 불구하고 실천 현장에서 과연 노인들에게 고유의 역할과 기능을 하고 있느냐 하는 관점에서 출발하고 있다. 특히 농어촌 거주 노인들의 경우 평소 여가활용 기회가 부족한 상황에서 지난 10년간 전국의 노인복지관 관련 수가 획기적으로 증가하였음에도 노인복지관 역할과 위상이 동일하게 여겨지고 있는가하는 점은 의구심을 불러일으키고 있다. 이에 도농형 도시 김포시에 거주하는 만 65세 이상 노인 360명을 대상으로 실태조사를 하였다. 연구방법으로 앤더슨 모형의 선행요인과 가능요인, 욕구요인간의 영향과 관계를 검증하고자 로짓분석 및 의사결정나무분석을 시행하였다. 연구결과 로짓분석에서는 앤더슨 모형에서 제시한 대부분의 요인들이 통계적으로 유의미하였다. 선행요인에서는 성별, 연령, 교육수준이, 가능요인에서는 월평균소득이, 욕구요인에서는 노후를 위한 경제자금준비와 경제활동준비가 유의미하였다. 다음으로 요인간 상호작용을 감안한 의사결정나무분석 시행 결과, 선행요인 중 교육수준이 높은 경우 노인복지관을 이용할 가능성이 가장 높았으며, 다음으로 욕구요인 중 건강증진 준비수준이 낮은 경우 노인복지관을 이용할 가능성이 높게 예측되었다. 이상과 같은 연구결과에 근거하여 노인복지관의 종합적 서비스 제공의 필요성을 제안하였다.