• Title/Summary/Keyword: decision trees

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A study on removal of unnecessary input variables using multiple external association rule (다중외적연관성규칙을 이용한 불필요한 입력변수 제거에 관한 연구)

  • Cho, Kwang-Hyun;Park, Hee-Chang
    • Journal of the Korean Data and Information Science Society
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    • v.22 no.5
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    • pp.877-884
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    • 2011
  • The decision tree is a representative algorithm of data mining and used in many domains such as retail target marketing, fraud detection, data reduction, variable screening, category merging, etc. This method is most useful in classification problems, and to make predictions for a target group after dividing it into several small groups. When we create a model of decision tree with a large number of input variables, we suffer difficulties in exploration and analysis of the model because of complex trees. And we can often find some association exist between input variables by external variables despite of no intrinsic association. In this paper, we study on the removal method of unnecessary input variables using multiple external association rules. And then we apply the removal method to actual data for its efficiencies.

Determining Factors of Intention to Actual Use of Charged Long-term Care Services for the Aged (유료노인장기요양보호서비스 이용의사 결정요인)

  • Yoo, Jin-Yeong;Chun, Jin-Ho
    • Journal of Preventive Medicine and Public Health
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    • v.38 no.1
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    • pp.16-24
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    • 2005
  • Objectives : To help develop strategies to cope with the changes arising from the rapid aging process by predicting the determining factors of intention to actual use of the charged long-term care services for elderly as perceived by the middle aged who play the major role of supports. Methods : Subjects were the parents (men 177, women 507) in their 40s of the students selected from a university of Busan city. A questionnaire survey was conducted for 4 weeks in October 2003 about the knowledge for long-term care service, the intention of actual use, and the preferences about the type of service suppliers. Data analysis was performed with frequency, chi-square test, and t-test using SPSS program (ver 10.0K), along with data mining using decision tree of Enterprise Miner V8.2 by SAS. Results : About half of the subjects (53.7%) had the actual experiences of elderly supports. Intentions to use the charged services were relatively high in home visiting nursing care service (40.1%) and long-term care facilities service (40.4%), and were influenced by previous knowledge about the services. The intentions were stronger in women, those with higher education, and those with greater income levels. Actual elderly supports were mostly (80%) done by women, and the perceived burdens for the supports were bigger in women and those of lower socioeconomic level. Desired charges were about 10,000 won for the bath service, 20,000 won for the rests services per day, and about 500,000 won for the long-term care facilities service per month. From the result of decision tree analysis, the job professionalism was the most important determining factor of intention to actual use of the services with validation as $63{\sim}71%$. Health and welfare mixed type facilities were preferred, and the most important consideration was the level of professionalism. Conclusions : Intention to actual use of the charged services was largely determined by the aspects of time and cost. Polices to increase the number of service suppliers and to decrease the burdens perceived by actual supporters were strongly recommended.

Analysis of periodontal health related factors by using data mining method (데이터 마이닝 기법을 이용한 치주건강 관련요인 분석연구)

  • Park, Hee-Jung;Lee, Jun Hyup;Kim, Tae-Il
    • The Journal of Korean Society for School & Community Health Education
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    • v.14 no.3
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    • pp.15-26
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    • 2013
  • Objectives: The purpose of this study was to evaluate self-reported symptoms of periodontal diseases. We performed a comprehensive analysis of periodontal health related factors. Methods: 581 volunteers representing a broad range of age from 20 to 65 were recruited from Seoul and Gyeonggi provinces. They participated in a self-administered survey of which the results were analyzed through the decision tree analysis using the data mining program. Results: 67% of the participants reported 'bad breath,' whereas 13.9% of participants reported 'toothache'. The decision analysis revealed that age was the most determining factor of adult periodontal health. Participants in 20s with a profound understanding of their periodontal health status exhibited a low vulnerability to periodontal diseases, whereas those lacking the awareness were more susceptible to the diseases. However, other participants in 30s and older showed a higher vulnerability to periodontal illness than those in 20s, whether or not they had suffered from chronic diseases. Conclusions: In order to effectively prevent periodontal diseases, an age-appropriate clinical approach will be necessary. For the younger age group it will be crucial to enhance the self-awareness of their current oral health status. On the other hand, those in 30s and older will need to pay a close attention to the prevention of chronic periodontal disease.

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Extraction of Blood Velocity Using FCM and Fuzzy Decision Trees in Doppler Ultrasound Images of Brachial Artery (상완동맥 색조 도플러 초음파 영상에서 FCM과 퍼지 의사 결정 트리를 이용한 혈류 속도 추출)

  • Kim, Kwang Baek;Jung, Young Jin;Nam, Youn Man;Lee, Jae Yeol
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2019.07a
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    • pp.19-22
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    • 2019
  • 상완동맥은 어깨에서부터 팔꿈치까지 내려오는 상완골의 내측부에 존재하며 혈압을 측정할 때 사용되는 혈관이다. 이 혈관은 골절로 인해 찢어지거나, 또는 혈액순환에 문제가 생겨 혈관이 막히는 경우가 발생한다. 이러한 경우 혈관의 상태를 확인하기 위하여 색조 도플러 초음파 검사를 사용하지만, 사용자에 따라 영상을 통한 판단 기준이 다르다는 문제점이 발생한다. 따라서 본 논문에서는 FCM과 Fuzzy Decision Tree를 이용한 영상 처리를 통해 일관성 있는 판단기준을 세우기 위한 혈류의 속도를 제안한다. 색조 도플러 초음파 영상에서의 상완 동맥을 추출하여 기울기를 이용한 FCM 알고리즘을 통해 소속도를 추출한 뒤 퍼지 룰에 적용하여 의사 결정 트리로 등급을 분류하고 결과적으로 혈류 속도를 추출한다. 색조 도플러 초음파 영상에서 환자의 개인 정보를 보호하기 위해 개인 정보 영역을 제거하여 ROI 영역을 추출하고 ROI 영역을 이진화를 통하여 상완동맥이 있는 영역을 추출한다. 이진화 된 ROI 영역에서 혈관 영상의 혈류 방향으로의 무게중심을 설정하고 각각의 픽셀과 무게중심 선과의 거리를 이용하여 소속도를 추출한 후 FCM을 사용하여 최적의 기울기를 선정한다. FCM을 통해 추출한 최종 소속도를 이용하여 퍼지 룰에 적용한 뒤 계산된 T-norm과 소속도의 분산을 이용하여 의사 결정 트리를 형성 트리의 단말 노드들은 각 픽셀을 분류한다. 분류되어진 데이터들의 노드별 소속도 평균을 구한 뒤 디퍼지화를 통해 COG(Center of Gravity)를 계산한다. 마지막으로 그 값을 이용하여 혈류 속도에 영향을 미치는 정도를 계산한 뒤 최종 혈류의 속도를 제안한다.

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Identification of High-risk Groups of Suicide from the Depressed Elderly using Decision Tree Analysis (의사결정나무 분석법을 이용한 우울 노인 중 자살 고위험군 규명)

  • Hong, Sehoon;Lee, Dongwon
    • Research in Community and Public Health Nursing
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    • v.30 no.2
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    • pp.130-140
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    • 2019
  • Purpose: The aim of this study is to explore levels of suicidal ideation and identify subgroups of high suicidal risk among the depressed elderly in Korea. Methods: A descriptive cross-sectional design was adopted on secondary data from the 6th (1st year) Korean national health and nutrition examination survey (KNHANES). A total of 239 depressed elders aged 60 or over who participated in the KNHANES. The prevalence of suicidal ideation and its related factors, including sociodemographic, physical, psychological characteristics and quality of life (EQ-5D index) were examined. Descriptive statistics and a decision tree analysis were performed using the SPSS/WIN 23.0 and SPSS Modeler 14.2 programs. Results: Of the depressed elderly, 28.9% had suicidal ideation. Three groups with high suicidal ideation were identified. Predictive factors included perceived stress level, household income level, quality of life and restriction of activity. In the highest risk group were those depressed elderly with moderate and low levels of stress, less than .71 of EQ-5D index and restriction of activity, and 80.0% of these participants had suicidal ideation. The accuracy of the model was 80.8%, its sensitivity 85.9%, and its specificity 68.1%. Conclusion: Multi-dimensional intervention should be designed to decrease suicide among the depressed elderly, particularly focusing on subgroups with high risk factors. This research is expected to contribute itself to the policy design and solution building in the future as it suggests policy implications in preventing the suicide of the depressed elderly.

Application of Decision Trees for Prediction of Sugar Content and Productivity using Soil Properties for Actinidia arguta 'Autumn Sense'

  • Ha, Si-Young;Jung, Ji-Young;Park, Young-Ki;Kweon, Gi-Young;Lee, Sang-Yoon;Park, Jae-Hyeon;Yang, Jae-Kyung
    • Journal of agriculture & life science
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    • v.53 no.5
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    • pp.37-49
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    • 2019
  • Environmental conditions are important in increasing the fruit sugar content and productivity of the new cultivar Autumn Sense of Actinidia arguta. We analyzed various soil properties at experimental sites in South Korea. A Pearson's correlation analysis was performed between the soil properties and sugar content or productivity of Autumn Sense. Further, a decision tree was used to determine the optimal soil conditions. The difference in the fruit size, sugar content, and productivity of Autumn Sense across sites was significant, confirming the effects of soil properties. The decision tree analysis showed that a soil C/N ratio of over 11.49 predicted a sugar content of more than 7°Bx at harvest time, and soil electrical capacity below 131.83 µS/cm predicted productivity more than 50 kg/vine at harvest time. Our results present the soil conditions required to increase the sugar content or productivity of Autumn Sense, a new A. arguta cultivar in South Korea.

Identification of Subgroups with Poor Glycemic Control among Patients with Type 2 Diabetes Mellitus: Based on the Korean National Health and Nutrition Examination Survey from KNHANES VII (2016 to 2018) (제 2형 성인 당뇨병 유병자의 혈당조절 취약군 예측: 제7기(2016-2018년도) 국민건강영양조사 자료 활용)

  • Kim, Hee Sun;Jeong, Seok Hee
    • Journal of Korean Biological Nursing Science
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    • v.23 no.1
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    • pp.31-42
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    • 2021
  • Purpose: This study was performed to assess the level of blood glucose and to identify poor glycemic control groups among patients with type 2 diabetes mellitus (DM). Methods: Data of 1,022 Korean type 2 DM patients aged 30-64 years were extracted from the Korea National Health and Nutrition Examination Survey VII. Complex samples analysis and a decision-tree analysis were performed using the SPSS WIN 26.0 program. Results: The mean level of hemoglobin A1c (HbA1c) was 7.22±0.25%, and 69.0% of the participants showed abnormal glycemic control (HbA1c≥6.5%). The characteristics of participants associated with poor glycemic control groups were presented with six different pathways by the decision-tree analysis. Poor glycemic control groups were classified according to the patients' characteristics such as period after DM diagnosis, awareness of DM, sleep duration, gender, alcohol drinking, occupation, income status, low density lipoprotein-cholesterol, abdominal obesity, and number of walking days per week. Period of DM diagnosis with a cut-off point of 6 years was the most significant predictor of the poor glycemic control group. Conclusion: The findings showed the predictable characteristics of the poor glycemic control groups, and they can be used to screen the poor glycemic control groups among adults with type 2 DM.

Retrospective analysis of the effects of non-communicable diseases on periodontitis treatment outcomes

  • Kim, Eun-Kyung;Kim, Hyun-Joo;Lee, Ju-Youn;Park, Hae-Ryoun;Cho, Youngseuk;Noh, Yunhwan;Joo, Ji-Young
    • Journal of Periodontal and Implant Science
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    • v.52 no.3
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    • pp.183-193
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    • 2022
  • Purpose: We retrospectively analysed patients' dental and periodontal status according to the presence of non-communicable diseases (NCDs) and the effects of NCDs on periodontal treatment outcomes. Factors influencing disease recurrence were investigated using decision tree analysis. Methods: We analysed the records of patients who visited the Department of Periodontology, Pusan National University Dental Hospital from June 2014 to October 2019. As baseline subjects, 1,362 patients with periodontitis and who underwent full-mouth periodontal examinations before periodontal treatment were selected. Among them, 321 patients who underwent periodontal examinations after the completion of periodontal treatment and 143 who continued to participate in regular maintenance were followed-up. Results: Forty-three percent of patients had a NCD. Patients without NCDs had more residual teeth and lower sum of the number of total decayed, missing, filled teeths (DMFT) scores. There was no difference in periodontal status according to NCD status. Patients with a NCD showed significant changes in the plaque index after periodontal treatment. The decision tree model analysis demonstrated that osteoporosis affected the recurrence of periodontitis. Conclusions: The number of residual teeth and DMFT index differed according to the presence of NCDs. Patients with osteoporosis require particular attention to prevent periodontitis recurrence.

The Primary Process and Key Concepts of Economic Evaluation in Healthcare

  • Kim, Younhee;Kim, Yunjung;Lee, Hyeon-Jeong;Lee, Seulki;Park, Sun-Young;Oh, Sung-Hee;Jang, Suhyun;Lee, Taejin;Ahn, Jeonghoon;Shin, Sangjin
    • Journal of Preventive Medicine and Public Health
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    • v.55 no.5
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    • pp.415-423
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    • 2022
  • Economic evaluations in the healthcare are used to assess economic efficiency of pharmaceuticals and medical interventions such as diagnoses and medical procedures. This study introduces the main concepts of economic evaluation across its key steps: planning, outcome and cost calculation, modeling, cost-effectiveness results, uncertainty analysis, and decision-making. When planning an economic evaluation, we determine the study population, intervention, comparators, perspectives, time horizon, discount rates, and type of economic evaluation. In healthcare economic evaluations, outcomes include changes in mortality, the survival rate, life years, and quality-adjusted life years, while costs include medical, non-medical, and productivity costs. Model-based economic evaluations, including decision tree and Markov models, are mainly used to calculate the total costs and total effects. In cost-effectiveness or costutility analyses, cost-effectiveness is evaluated using the incremental cost-effectiveness ratio, which is the additional cost per one additional unit of effectiveness gained by an intervention compared with a comparator. All outcomes have uncertainties owing to limited evidence, diverse methodologies, and unexplained variation. Thus, researchers should review these uncertainties and confirm their robustness. We hope to contribute to the establishment and dissemination of economic evaluation methodologies that reflect Korean clinical and research environment and ultimately improve the rationality of healthcare policies.

Resupply Behavior Modeling in Small-unit Combat Simulation using Decision Trees (소부대 전투 모의를 위한 의사결정트리 기반 재보급 행위 모델링)

  • Seil An;Sang Woo Han
    • Journal of the Korea Society for Simulation
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    • v.32 no.3
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    • pp.9-21
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    • 2023
  • The recent conflict between Russia and Ukraine underscores the significant of military logistics support in modern warfare. Military logistics support is intricate and specialized, and traditionally centered on the mission-level operational analysis and functional models. Nevertheless, there is currently increasing demand for military logistics support even at the engagement level, especially for resupply using unmanned transport assets. In response to the demand, this study proposes a task model of the military logistics support for engagement-level analysis that relies on the logic of ammunition resupply below the battalion level. The model employs a decisions tree to establish the priority of resupply based on variables such as the enemy's level of threat and the remaining ammunition of the supported unit. The model's feasibility is demonstrated through a combat simulation using OneSAF.