• Communications for Statistical Applications and Methods
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• 제8권3호
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• pp.823-829
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• 2001

Even though a rapid development of modem medical science, paralysis disease is a highly dangerous and murderous disease. Shin et al. (1978) constructed the diagnosis expert system which identify a type of the paralysis disease from symptoms of a paralysis disease patients by using the canonical discriminant analysis. The decision tree-based analysis, however, has advantages over the method used in Shin et al. (1998), such as it does not need assumptions - linearity and normality, and suggest appropriate diagnosis procedure which is easily explained. In this paper, we applied the decision tree to construct the model which Identify a type of the paralysis disease.

• Industrial Engineering and Management Systems
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• 제4권1호
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• pp.102-108
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• 2005

This paper studies medical data classification methods, comparing decision tree and system reconstruction analysis as applied to heart disease medical data mining. The data we study is collected from patients with coronary heart disease. It has 1,723 records of 71 attributes each. We use the system-reconstruction method to weight it. We use decision tree algorithms, such as induction of decision trees (ID3), classification and regression tree (C4.5), classification and regression tree (CART), Chi-square automatic interaction detector (CHAID), and exhausted CHAID. We use the results to compare the correction rate, leaf number, and tree depth of different decision-tree algorithms. According to the experiments, we know that weighted data can improve the correction rate of coronary heart disease data but has little effect on the tree depth and leaf number.

• International Journal of Computer Science & Network Security
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• 제24권2호
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• pp.150-154
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• 2024

In recent years, there are extensive researches on the applications of machine learning to the automation and decision support for medical experts during disease detection. However, the performance of machine learning still needs improvement so that machine learning model produces result that is more accurate and reliable for disease detection. Selecting the hyper-parameter that could produce the possible maximum classification accuracy on medical dataset is the most challenging task in developing decision support systems with machine learning algorithms for medical dataset classification. Moreover, selecting the features that best characterizes a disease is another challenge in developing machine-learning model with better classification accuracy. In this study, we have proposed an optimized decision tree model for heart disease classification by using heart disease dataset collected from kaggle data repository. The proposed model is evaluated and experimental test reveals that the performance of decision tree improves when an optimal number of features are used for training. Overall, the accuracy of the proposed decision tree model is 98.2% for heart disease classification.

• Journal of Ecology and Environment
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• 제35권4호
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• pp.359-365
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• 2012

We investigated leaf disease intensity of Kalopanax septemlobus (prickly castor oil tree) caused by the parasitic fungus Mycosphaerella acanthopanacis, in thirty natural host populations in the Japanese Archipelago. The disease intensity observed for individual trees were analyzed using a generalized additive model as a function of tree size, tree density, climatic terms and spatial trend surface. Individual tree size and conspecific tree density were shown to have significant negative and positive effects on disease intensity, respectively. The findings suggest that the probability of disease infection is partly determined by dispersal of infection agents (ascospores) from the fallen leaves on the ground, which can be enhanced by aggregation of host trees in a forest stand. Regional-scale spatial bias was also present in disease intensity; the populations in northern Japan and southern Kyushu were more severely infected by the fungus than those in southwestern Honshu and Shikoku. Regional variation of disease intensity was explained by both climatic factors and a trend surface term, with a latitudinal cline detected, which increases towards the north. Further research should be conducted in order to understand all of the factors generating the latitudinal cline detected in this study.

• The Plant Pathology Journal
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• 제30권1호
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• pp.43-50
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• 2014

Microorganisms have many roles in nature. They may act as decomposers that obtain nutrients from dead materials, while some are pathogens that cause diseases in animals, insects, and plants. Some are symbionts that enhance plant growth, such as arbuscular mycorrhizae and nitrogen fixation bacteria. However, roles of plant pathogens and diseases in natural ecosystems are still poorly understood. Thus, the current study addressed this deficiency by investigating possible roles of plant diseases in natural ecosystems, particularly, their positive effects on arthropod diversity. In this study, the model system was the oak tree (Quercus spp.) and the canker disease caused by Annulohypoxylon truncatum, and its effects on arthropod diversity. The oak tree site contained 44 oak trees; 31 had canker disease symptoms while 13 were disease-free. A total of 370 individual arthropods were detected at the site during the survey period. The arthropods belonged to 25 species, 17 families, and seven orders. Interestingly, the cankered trees had significantly higher biodiversity and richness compared with the canker-free trees. This study clearly demonstrated that arthropod diversity was supported by the oak tree canker disease.

• 조경수
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• 통권128호
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• pp.16-21
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• 2012

• 조경수
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• 통권137호
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• pp.32-35
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• 2013

• Journal of Ecology and Environment
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• 제38권1호
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• pp.85-93
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• 2015

In 2013, the epidemics of pine wilt disease caused by the pine wood nematodes (Bursaphelenchus xylophilus) resulted in damages to the forests of black pine (Pinus thunbergii Parl.) trees in Jeju Island, Korea. Among the affected trees, an old black pine tree at Cave Temple on Mt. Sanbangsan was included and died due to the prevalence of pine wilt disease. The tree was on Mt. Sanbangsan, which was designated as a National Scenic Place with the Number 77 and was believed to be more than 400 years old in age. By examining the disc of the tree stem obtained from the height of 2 m, we counted the tree rings from 4 different directions and cross-dated the readings by comparing the records of drought simulated from the BROOK Model. Our analysis indicates that the tree seems to have grown since late 1860s. Contrary to the belief of the general public, we can conclude that the age of the tree was estimated to be at maximum 150 years, which means that it was not the same old tree as was shown in the painting of the Tam-Ra-Sun-Ryeok-Do (an old painting book for the Inspection Tour of Jeju Island) published in 1702. Discussion was extended to the life history of the tree in growth and leaning and the measures to protect the tree species from the damages of the pine wilt disease caused by pine wood nematodes.

• 한국컴퓨터정보학회논문지
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• 제27권5호
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• pp.21-28
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• 2022

심혈관질환은 심장질환과 혈관질환 등 순환기계통에 생기는 모든 질병을 통칭한다. 심혈관질환은 2019년 사망의 1/3을 차지하는 전 세계 사망의 주요 원인이며, 사망자는 계속 증가하고 있다. 이와 같은 질병을 인공지능을 활용해 환자의 데이터로 미리 예측이 가능하다면 질병을 조기에 발견해 치료할 수 있을 것이다. 본 연구에서는 심혈관질환 중 하나인 심장질환을 예측하는 모델들을 생성하였으며 Accuracy, Precision, Recall의 측정값을 지표로 하여 모델들의 성능을 비교한다. 또한 Decision Tree의 성능을 향상시키는 방법에 대해 기술한다. 본 연구에서는 macOS Big Sur환경에서 Jupyter Notebook으로 Python을 사용해 scikit-learn, Keras, TensorFlow 라이브러리를 이용하여 실험을 진행하였다. 연구에 사용된 모델은 Decision Tree, KNN(K-Nearest Neighbor), SVM(Support Vector Machine), DNN(Deep Neural Network)으로 총 4가지 모델을 생성하였다. 모델들의 성능 비교 결과 Decision Tree 성능이 가장 높은 것으로 나타났다. 본 연구에서는 노드의 특성배치를 변경하고 트리의 최대 깊이를 3으로 지정한 Decision Tree를 사용하였을 때 가장 성능이 높은 것으로 나타났으므로 노드의 특성 배치 변경과 트리의 최대 깊이를 설정한 Decision Tree를 사용하는 것을 권장한다.

• 디지털콘텐츠학회 논문지
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• 제18권1호
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• pp.191-195
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• 2017

본 연구에서는 우리나라의 대표수종 소나무의 치명적인 해충인 소나무재선충 피해목의 확산을 조기에 차단하고 산림수목에 대한 지속적인 관리를 위하여 소나무재선충 피해수목 신고 어플리케이션을 개발하였다. 어플리케이션은 다음과 같이 3개 핵심항목을 중심으로 개발되었다. 첫째, 소나무재선충에 대한 정보제공, 둘째, 피해목의 자가진단, 셋째, 수목안전지도 등으로 구성하였다. 향후 본 어플리케이션의 활성화를 위해서 실제로 어플리케이션을 사용하는 이용자들의 적극적인 참여와 산림청 어플리케이션과의 통합개발이 이뤄진다면 보다 많은 활용이 가능할 것이다.