• International Journal of Highway Engineering
• /
• v.20 no.3
• /
• pp.27-37
• /
• 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
• /
• v.11 no.3
• /
• pp.285-295
• /
• 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
• /
• v.12 no.2
• /
• pp.80-91
• /
• 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.

• Korean Journal of Oriental Medicine
• /
• v.17 no.2
• /
• pp.121-127
• /
• 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.

• International Journal of Highway Engineering
• /
• v.11 no.2
• /
• pp.37-44
• /
• 2009

Currently the reasonability of threshold values for rutting and cracking does not clearly defined at the Pavement Rehabilitation Decision Tree on national highway PMS(Pavement Management System). The goal of this study is to provide the reasonable threshold values for the national highway asphalt concrete pavement rehabilitation. To achieve this goal, test section that represents typical asphalt concrete pavement of national highway was selected and pavement export were participated. Pavement condition survey has been conducted and pavement performance data at the selected roadway section were analyzed. From this study, reasonable threshold values of Pavement Rehabilitation Decision Tree were suggested based on the pavement expert's engineering judgement. In terms of crack repairs, the application of overlay after cutting is required to deteriorated area where existing crack ratio is over 35% and just overlay is required to where crack ratio is over 20%. On rutting, rut depth over 13mm is required to overlay after cutting and rut depth over 10mm is just needed to overlay.

• Journal of the Institute of Electronics Engineers of Korea CI
• /
• v.48 no.2
• /
• pp.28-37
• /
• 2011

With growing concerns about healthy life recently, although the podiatry which deals with the whole area for diagnosis, treatment of foot and leg, and prevention has been widely interested, research in our country is not active. Also, because most of the previous researches in data analysis performed the quantitative approaches, the reasonable level of reliability for clinical application could not be guaranteed. Clinical data mining utilizes various data mining analysis methods for clinical data, which provides decision support for expert's diagnosis and treatment for the patients. Because the decision tree can provide good explanation and description for the analysis procedure and is easy to interpret the results, it is simple to apply for clinical problems. This study investigate rules of item of diagnosis in disease types for adapting decision tree after collecting diagnosed data patients who are 2620 feet of 1310(males:633, females:677) in shoes clinic (department of rehabilitation medicine, Chungnam National University Hospital). and we classified 15 foot diseases followed factor of 22 foot diseases, which investigated diagnosis of 64 rules. Also, we analyzed and compared correlation relationship of characteristic of disease and factor in types through made decision tree from 5 class types(infants, child, adolescent, adult, total). Investigated results can be used qualitative and useful knowledge for clinical expert`s, also can be used tool for taking effective and accurate diagnosis.

• The Journal of Korean Medicine
• /
• v.33 no.4
• /
• pp.1-8
• /
• 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.

• Korean Journal of Construction Engineering and Management
• /
• v.12 no.6
• /
• pp.101-109
• /
• 2011

As climate change is becoming the main issue, various efforts are focused on saving building energy consumption both at home and abroad. In particular, it is very important to save energy by maintenance, repair and rehabilitation of existing multi-family housing complex, because energy consumption in residential buildings is not only forming a great part of gross energy consumption in Korea but the number of deteriorated complexes is also sharply increasing. However, energy saving is not considered as a main factor in decision making on rehabilitation project. Also, any supporting tool is not appropriately prepared in existing process. As the first step for development of decision support system on rehabilitation, this paper developed a breakdown structure, which makes clusters of multi-family housing complexes. Decision tree, one of data mining methods, was used to make clusters based on the characteristics and energy consumption data of multi-family housing complexes. Energy saving and CO2 reduction will be maximized by considering energy consumption during rehabilitation process of multi-family housing complex, based on these results and following research.

• Health Policy and Management
• /
• v.26 no.4
• /
• pp.289-304
• /
• 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
• /
• v.38 no.2
• /
• pp.351-364
• /
• 2018

The purpose of this study is to learn about the decision factors affecting utilization of elderly welfare center of the elderly living in Gimpo city. The reason of the study is that the elderly welfare center as a provider of general welfare services could not only thinking about the state policy but also need to consider about the inherent role and function of the elderly. Especially for these elders living in rural areas, although the number of elderly welfare centers of the whole country has greatly increased in last 10 years, the effect and function of the facility are almost the same and they are still lack of leisure activities. This issue become a serious problem nowadays. For the above reasons, this article conducts a social survey of 360 elderly people over the age of 65 who lives in the Gimpo city which is a rural-urban type city. The research method is to examine the relationship between the predisposing factors, enabling factors and need factors of Andersen's behavior model with binary logistic regression analysis and the decision tree analysis. The result of binary logistic regression shows the most of factors of Andersen's model is significant. The factors of age, gender, education level in predisposing factors; monthly income in enabling factors and the reserve for old life, the preparation of economic activity for old life in need factors are significant. Then the result of decision tree analysis shows the interaction between factors; when the education level in predisposing factors is higher, the possibility of using of elderly welfare center becomes bigger. Also as the level of healthy promoting preparation in the need factors gets lower, the possibility of using of elderly welfare center still becomes bigger. Although differences were found in the interpretation of the results of regression analysis and decision tree analysis, the results of this study can still provide support for the necessity of elderly welfare centers providing integrated welfare services.