• 대한수학회지
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• 제54권3호
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• pp.987-997
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• 2017

A deterministic model for the spread of pine wilt disease with asymptomatic carrier trees in the host pine population is designed and rigorously analyzed. We have taken four different classes for the trees, namely susceptible, exposed, asymptomatic carrier and infected, and two different classes for the vector population, namely susceptible and infected. A complete global analysis of the model is given, which reveals that the global dynamics of the disease is completely determined by the associated basic reproduction number, denoted by $\mathcal{R}_0$. If $\mathcal{R}_0$ is less than one, the disease-free equilibrium is globally asymptotically stable, and in such a case, the endemic equilibrium does not exist. If $\mathcal{R}_0$ is greater than one, the disease persists and the unique endemic equilibrium is globally asymptotically stable.

• 한국멀티미디어학회논문지
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• 제21권2호
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• pp.271-280
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• 2018

Recently, big data has been growing rapidly due to the development of IT technology. Especially in the medical field, big data is utilized to provide services such as patient-customized medical care, disease management and disease prediction. In Korea, 'National Health Alarm Service' is provided by National Health Insurance Corporation. However, the prediction model has a problem of short-term prediction within 3 days and unreliability of social data used in prediction model. In order to solve these problems, this paper proposes a disease prediction model using medicine prescription data generated from actual patients. This model predicts the total number of patients and the risk of disease in each region and uses the ARIMA model for long-term predictions.

• 대한간호학회지
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• 제40권4호
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• pp.580-588
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• 2010

Purpose: The purpose of this study was to examine effects of decreased locomotor activity on mass, Type I and II fiber cross-sectional areas of ipsilateral and contralateral hindlimb muscles 21 days after establishing the Parkinson's disease rat model. Methods: The rat model was established by direct injection of 6-hydroxydopamine (6-OHDA, 50 ${mu}g$) into the left substantia nigra after stereotaxic surgery. Adult male Sprague-Dawley rats were assigned to one of two groups; the Parkinson's disease group (PD; n=17) and a sham group (S; n=8). Locomotor activity was assessed before and 21 days after the experiment. At 22 days after establishing the rat model, all rats were anesthetized and soleus and plantaris muscles were dissected from both ipsilateral and contralateral sides. The brain was dissected to identify dopaminergic neuronal death of substantia nigra in the PD group. Results: The PD group at 21 days after establishing the Parkinson's disease rat model showed significant decrease in locomotor activity compared with the S group. Weights and Type I and II fiber cross-sectional areas of the contralateral soleus muscle of the PD group were significantly lower than those of the S group. Conclusion: Contralateral soleus muscle atrophy occurs 21 days after establishing the Parkinson's disease rat model.

• 한국측량학회지
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• 제31권3호
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• pp.209-219
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• 2013

역학 모델은 질병 확산에 대한 시뮬레이션 및 관련 방역대책을 수립하는데 유용하며, 개체들의 접촉을 통해 전파되는 질병의 공간 확산에 대한 자세한 이해를 가능하게 한다. 이 연구에서는 공간에서 개체 간의 상호작용에 의한 결과로 구제역 전염병의 확산을 시뮬레이션하기 위해 GIS와 통합된 행위자 기반 공간 모델을 제안하고자 한다. 설계된 모델은 모집단, 시간, 공간이라는 세 요소를 고려하여 축산장 간의 간접접촉을 묘사하였다. 모집단의 역학관계는 2010년 경상북도 안동시에서 발생한 구제역 사례를 기준으로 하였으며, 도로를 주행하는 차량에 의한 간접접촉으로 전염병이 전파하는 것으로 설계하였다. 확산 모델은 구제역 전파 확률, 질병에 대한 여러 상태, 질병의 확산 시간, 감염률, 잠복기 및 기타 매개변수 간의 관계를 수식으로 표현하였다. 모델을 이용하여 구제역 발생 상황을 예측하면서 다양한 시나리오를 적용해서 모의실험하였다. 구제역 발생 상황에서 방역 전략을 선정하기 위해 제시된 방법을 이용하여 방역조치를 다양하게 실험하는 것은 구제역 확산을 통제하는 데 중요한 역할을 할 것으로 기대된다.

• 동의생리병리학회지
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• 제23권6호
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• pp.1460-1464
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• 2009

In spite of many studies on statistical model for pattern identifications (PIs), little attention has been paid to the complexity of pattern diagnosis processed by oriental physicians. The aim of this study is to develop a statistical diagnostic model which discriminates four PIs using multiple indicators in stroke. Clinical data were collected from 981 stroke patients and 516 data of which PIs were agreed by two independent physicians were included. Discriminant analysis was carried out using clinical indicators such as symptoms and signs which referred to pattern diagnosis, and applied to validation samples which contained all symptoms and signs manifested. Four Fischer's linear discriminant models were derived and their accuracy and prediction rates were 93.2% and 80.43%, respectively. It is important to consider the pattern diagnosis processed by oriental physicians in developing statistical model for PIs. The discriminant model developed in this study using multiple indicators is valid, and can be used in the clinical fields.

• 한국컴퓨터정보학회논문지
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• 제21권3호
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• pp.65-71
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• 2016

To reduce the expenses for development a novel drug, systems biology has been studied actively. Target prediction, a part of systems biology, contributes to finding a new purpose for FDA(Food and Drug Administration) approved drugs and development novel drugs. In this paper, we propose a classification model for predicting novel target genes based on relation between target genes and disease related genes. After collecting known target genes from TTD(Therapeutic Target Database) and disease related genes from OMIM(Online Mendelian Inheritance in Man), we analyzed the effect of target genes on disease related genes based on PPI(Protein-Protein Interactions) network. We focused on the distinguishing characteristics between known target genes and random target genes, and used the characteristics as features for building a classifier. Because our model is constructed using information about only a disease and its known targets, the model can be applied to unusual diseases without similar drugs and diseases, while existing models for finding new drug-disease associations are based on drug-drug similarity and disease-disease similarity. We validated accuracy of the model using LOOCV of ten times and the AUCs were 0.74 on Alzheimer's disease and 0.71 on Breast cancer.

• 스마트미디어저널
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• 제13권6호
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• pp.90-97
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• 2024

This paper focuses on detecting Alzheimer's Disease (AD). The most usual form of dementia is Alzheimer's disease, which causes permanent cause memory cell damage. Alzheimer's disease, a neurodegenerative disease, increases slowly over time. For this matter, early detection of Alzheimer's disease is important. The purpose of this work is using Magnetic Resonance Imaging (MRI) to diagnose AD. A Convolution Neural Network (CNN) model, Reset, and VGG the pre-trained learning models are used. Performing analysis and validation of layers affects the effectiveness of the model. T1-weighted MRI images are taken for preprocessing from ADNI. The Dataset images are taken from the Alzheimer's Disease Neuroimaging Initiative (ADNI). 3D MRI scans into 2D image slices shows the optimization method in the training process while achieving 96% and 94% accuracy in VGG 16 and ResNet 18 respectively. This study aims to classify AD from brain 3D MRI images and obtain better results.

• 대한간호학회지
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• 제31권3호
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• pp.477-491
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• 2001

Purpose: This study was designed to construct a structural model for health promoting behavior in patients with chronic respiratory disease. A hypothetical model was developed based on the literature review. Method: Data was collected by questionnaires from 235 patients with chronic respiratory disease in a General Hospital in Seoul. Data analysis was done using SAS 6.12 for descriptive statistics and the PC-LISREL 8.13 Program for Covariance Structural Analysis. Result: The results are as follows : 1. The fit of the hypothetical model to the data was moderate. It was modified by excluding 2 path and including free parameters and 3 path to it. The modified model with path showed a good fitness to the empirical data($\chi$2=80.20, P=0.05, GFI=0.95, AGFI=0.88, NNFI=0.95, NFI=0.96, RMSR=0.01, RMSEA =0.06). 2. The perceived benefits, self-efficacy, and a plan of action were found to have significant direct effects on the health promoting behavior in patients with chronic respiratory disease. 3. The health perception, self-esteem, and activity related to affect were found to have indirect effects on the health promoting behavior in patients with chronic respiratory disease. Conclusion: The modified model of this study is considered appropriate in explaining and predicting health promoting behavior in patients with chronic respiratory disease. Therefore, it can effectively be used as a reference model for further studies and suggested direction in nursing practice.

• International Journal of Computer Science & Network Security
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• 제22권6호
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• pp.223-229
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• 2022

Early detection can help prevent heart disease, which is one of the most common reasons for death. This paper provides a clinical support model for predicting cardiac disease. The model is built using two publicly available data sets. The admissibility and application of the the model are justified by a sequence of tests. Implementation of the model and testing are also discussed

• 대한간호학회지
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• 제31권1호
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• pp.107-125
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• 2001

This study was designed to construct a structural model for quality of life of chronic gastric disease. The hypothetical model was developed based on the literature review and Pender's health promotion model. Data were collected by questionnaires from 459 patients with chronic gastric disease in a General Hospital from July 1999 to August 2000 in Seoul. Data analysis was done with SAS 6.12 for descriptive statistics and PC-LISREL 8.13 Program for Covariance structural analysis. The results are as follows : 1. The fit of the hypothetical model to the data was moderate, thus it was modified by excluding 1 path and including free parameters and 2 path to it. The modified model with path showed a good fitness to the empirical data ($\chi$2=934.87, p<.0001, GFI=0.88, AGFI=0.83, NNFI=0.86, RMSR =0.02, RMSEA=0.07). 2. The perceived barrier, health promoting behavior, self-efficacy, and self-esteem were found to have significant direct effects on the quality of life. 3. The health concept, health perception, emotional state, and social support were found to have indirect effects on quality of life of chronic gastric disease. In conclusion, the derived model in this study is considered appropriate in explaining and predicting quality of life of chronic gastric disease. Therefore it can effectively be used as a reference model for further studies and suggested direction in nursing practice.