• Title/Summary/Keyword: Tree doctor

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Legalization of Tree Doctor System and the Role of KSPP (나무의사 제도 법제화에 따른 식물병리학회의 역할)

  • Cha, Byeongjin
    • Research in Plant Disease
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    • v.23 no.3
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    • pp.207-211
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    • 2017
  • In December of 2016, 'The Forest Protection Act' was amended partly in The National Assembly and the socalled 'Tree Doctor Act' was promulgated. Tree Doctor Act will be enforced from June 28, 2018. Under the new Act, none other than 'Tree Hospital' can do disease and pest management work for trees in public living space. The only exclusive qualification for tree hospital is a 'Tree Doctor', the government registered license which is newly established by the Act. To become a tree doctor, he/she must complete the tree doctor training courses in the designated 'Tree Doctor Academy' and pass the qualification test. Currently, Korea Forest Service is drafting the enforcement ordinances and regulations for the implement of Tree Doctor Act. When taking into consideration that the most fundamental and important discipline of the plant and tree health care is the plant pathology, and that the tree health care is a promising business for young plant pathology people, Korean Society of Plant Pathology is ought to be actively involved in the preparation of the enforcement ordinances and regulations, and help the early establishment of the new tree health care system in living spaces of Korea.

Analysis of the Actual Condition of the Tree Doctor Qualification Test and Improvement of the System - Focus on the First Test - (나무의사 자격시험의 실태분석과 제도개선 방안 - 제1차 시험을 중심으로 -)

  • Yong Jo Jung;Hak Cheol Kim
    • Journal of Environmental Science International
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    • v.32 no.1
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    • pp.11-24
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    • 2023
  • This study aimed to provide preliminary data for the improvement of the tree doctor qualification test (first written test), which was newly created by enforcing the Forest Protection Act on June 28, 2018., The high demand for system improvement accelerated this study. The results were analyzeds through literature and questionnaire surveys. Writing test questions and the license of the tree doctor qualification exam are currently managed by the Korea Forestry Research Institute, and it is deemed that the test should be entrusted to Human Resources Development Service of Korea for fair and transparent management. Additionally, the plan for the improvement of the subject-wise scope of examination questions writing, difficulty of test questions, and acceptance rate of the first test should be prepared after public hearings or seminars related to the examination questions.

Telemedicine Security Risk Evaluation Using Attack Tree (공격트리(Attack Tree)를 활용한 원격의료 보안위험 평가)

  • Kim, Dong-won;Han, Keun-hee;Jeon, In-seok;Choi, Jin-yung
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.25 no.4
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    • pp.951-960
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    • 2015
  • The smart screening in the medical field as diffusion of smart devices and development of communication technologies is emerging some medical security concerns. Among of them its necessary to taking risk management measures to identify, evaluate and control of the security risks that can occur in Telemedicine because of the Medical information interchanges as Doctor to Doctor (D2D), Doctor to Patient (D2P). This research paper studies and suggests the risk analysis and evaluation methods of risk security that can occur in Telemedicine based on the verified results of Telemedicine system and equipment from the direct site which operating in primary clinics, public health centers and it's branches, etc.

A study of constitution diagnosis using decision tree method (의사결정나무법을 이용한 체질진단에 관한 연구)

  • Lee, Yong-Seop;Park, Seong-Sik;Park, Eun-Kyung
    • Journal of Sasang Constitutional Medicine
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    • v.13 no.2
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    • pp.144-155
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    • 2001
  • By the increasing concern about Sasang Constitution Medicine, its practical use is considered very important in disease prevention and medical treatment. However, the method of constitution classification is depending on the doctor's clinical trials because of the lack of the objective test criteria. This study is trying to improve the objectiveness of diagnosis using a new statistical method, decision tree. Decision tree method-a classification technique in the statistical analysis- was used to analyze the result of QSCCII instead of using discriminant analysis. As a result, 16 among 121 QSCCII questions was selected as important questions and 21 terminal nodes was built to classify the constitution. Using only 16 questions shown in the result of decision tree, we can diagnose and interpret the constitution easily and effectively.

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Oriental Medicine-based Health Pre-Diagnosis System using Fuzzy Decision Tree (퍼지 의사 결정 트리를 이용한 한의학 기반의 건강 사전 진단 시스템)

  • Kim, Kwang Baek
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.25 no.11
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    • pp.1519-1524
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    • 2021
  • In this paper, we propose a method that uses fuzzy decision tree based health pre-diagnosis system of oriental medicine. The proposed fuzzy decision tree based health pre-diagnosis system uses the data from the past which has been pre-trained to get the boundary values based on entropy then, when the user inputs the symptoms, the top 5 diseases that causes those symptoms are extracted. With the extracted top 5 diseases, the system provides information on those diseases with the cause and how to treat them with folk remedies. The database of the diseases and their symptoms is established with the information based on the various books that the oriental doctor recommended then reviewed by the oriental doctor for confirmation. By utilizing the data from the past to train the symptoms of the diseases, the proposed oriental medicine-based health pre-diagnosis system method could provide more accurate diagnosis results faster.

Convergence outpatient medical service patient experience research using data mining (데이터마이닝 기법을 이용한 융복합 외래 의료서비스 환자경험조사 연구)

  • Yoo, Jin-Yeong
    • Journal of Digital Convergence
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    • v.18 no.7
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    • pp.299-306
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    • 2020
  • The purpose of this study is to find out specific measures that can help the management strategy of patient-centered medical institutions by conducting research on patient experience surveys of convergence outpatient medical services using data mining techniques according to changes in patient-centered medical culture. Using the raw data of the 2018 Medical Service Experience Survey, 8,843 people over the age of 15 who had patient experience in outpatient medical services were analyzed. Decision tree analysis was performed. The determinants of satisfaction with outpatient medical services patient experience were the doctor's area and patient's rights protection area, and the determinants of intention to recommend outpatient medical services were the doctor's area and facilities comfort. Women evaluated the experience positively in overall satisfaction as compared to men, and those over the age of 60 positively evaluated the overall satisfaction and intention to recommend. It is significant that the outpatient experience decision-making model is presented, and that the doctor's area, patient's rights protection area, and facility comfort are important factors. Long-term research on the 'Medical Service Experience Survey' is needed, and research on the inpatient medical service experience is needed.

Decision-tree Model of Treatment-seeking Behaviors after Detecting Symptoms by Korean Stroke Patients

  • Oh Hyo-Sook;Park Hyeoun-Ae
    • Journal of Korean Academy of Nursing
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    • v.36 no.4
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    • pp.662-670
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    • 2006
  • Purpose. This study was performed to develop and test a decision-tree model of treatment-seeking behaviors about when Korean patients visit a doctor after experiencing stroke symptoms. Methods. The study used methodological triangulation. The model was developed based on qualitative data collected from in-depth interviews with 18 stroke patients. The model was tested using quantitative data collected from interviews and a structured questionnaire involving 150 stroke patients. The predictability of the decision-tree model was quantified as the proportion of participants who followed the pathway predicted by the model. Results. Decision outcomes of the model were categorized into immediate and delayed treatment-seeking behavior. The model was influenced by lowered consciousness, social-group influences, perceived seriousness of symptoms, past history of hypertension or stroke, and barriers to hospital visits. The predictability of the model was found to be 90.7%. Conclusions. The results from this study can help healthcare personnel understand the education needs of stroke patients regarding treatment-seeking behaviors, and hence aid in the development of educational strategies for stroke patients.

J48 and ADTree for forecast of leaving of hospitals

  • Halim, Faisal;Muttaqin, Rizal
    • Korean Journal of Artificial Intelligence
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    • v.4 no.1
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    • pp.11-13
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    • 2016
  • These days, medical technology has been developed rapidly to meet desire of living healthy life. Average lifespan was extended to let people see a doctor because of many reasons. This study has shown rate of leaving of hospitals to investigate the rate of not only department of surgery but also department of internal medicine. Linear model, tree, classification rule, association and algorithm of data mining were used. This study investigated by using J48 and AD tree of decision-making tree In this study, J48 and AD tree of decision-making tree of data mining were used to investigate based on result of both data. Both algorithms were found to have similar performance. Both algorithms were not equivalent to require detailed experiment. Collect more experimental data in the future to apply from various points of view. Development of medical technology gives dream, hope and pleasure. The ones who suffer from incurable diseases need developed medical technology. Environment being similar to the reality shall be made to experiment exactly to investigate data carefully and to let the ones of various ages visit hospital and to increase survival rate.

A Study of Pathogenesis Classification using Decision Tree Method (의사결정나무법을 이이용한 병인(病因)분류에 관한 연구)

  • Lee, Hyuk-Jae;Kim, Min-Yong;Oh, Hwan-Sup;Park, Young-Bae
    • The Journal of the Society of Korean Medicine Diagnostics
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    • v.12 no.2
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    • pp.27-40
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    • 2008
  • Background : In spite of the predominant of the theory of Pathogenesis, the method of Pathogenesis classification is depending on the doctor's clinical trials because od the lack of the objective test criteria. Methods and Results : This study is trying to improve the objectiveness of classification using a new statistical method, decision tree. Decision tree method -a classification technique in the statistical analysis- was used to analyze the result of pathogenesis questionnaire instead of using discriminant analysis. As a result, 10 among 38 pathogenesis questionnaire was selected as important questions and 12 terminal nodes was built to classify the pathogenesis. Conclusions : Using only 10 questions shown in the result of decision tree, we can classify and interpret the pathogenesis easily and effectively.

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Data Mining Approach to Clinical Decision Support System for Hypertension Management (고혈압관리를 위한 의사지원결정시스템의 데이터마이닝 접근)

  • 김태수;채영문;조승연;윤진희;김도마
    • Proceedings of the Korea Inteligent Information System Society Conference
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    • 2002.11a
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    • pp.203-212
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    • 2002
  • This study examined the predictive power of data mining algorithms by comparing the performance of logistic regression and decision tree algorithm, called CHAID (Chi-squared Automatic Interaction Detection), On the contrary to the previous studies, decision tree performed better than logistic regression. We have also developed a CDSS (Clinical Decision Support System) with three modules (doctor, nurse, and patient) based on data warehouse architecture. Data warehouse collects and integrates relevant information from various databases from hospital information system (HIS ). This system can help improve decision making capability of doctors and improve accessibility of educational material for patients.

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