• Korean Journal of Adult Nursing
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• v.20 no.1
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• pp.1-9
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• 2008

Purposes: This study examined uncertainty and nursing need according to illness phases(phase I, II, III) in cancer patients, and investigated relationships between uncertainty and nursing need. Methods: A cross-sectional descriptive study was conducted with a sample of 121 adult cancer patients treated in two hospitals. Results: As for the total score, the uncertainty was not significantly different across the subgroups by illness phase. As for the subscale score, however, two sub-scales of the uncertainty were different across the subgroups. 'The unpredictability' was highest in illness phase I and II groups, while 'the lack of information' was highest in the illness phase III group. Nursing need as the total score was not significantly different across the subgroups by illness phase. However, all subscale scores of the nursing need were significantly different across the subgroups. Educational need was highest in the illness phase I group; physical and emotional needs were highest in the illness phase III group. Uncertainty and nursing need were not related to each other at any illness phase. Conclusion: The results suggest that nursing need and uncertainty may change across illness phases. Clinicians need to consider this pattern in caring for cancer patients.

• Journal of Biomedical Engineering Research
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• v.22 no.2
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• pp.179-185
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• 2001

혈관에 발생하는 동맥 경화증은 그 발생 시기와 진행 정도를 예측하기 힘들어 초기 단계의 진단 및 치료가 어렵다. 이러한 이유로 혈관 질병의 진단은 많은 연구자들의 관심 대상이 되어왔고, 현재까지도 그 진단 장치 및 방법에 관한 연구가 활발히 진행되고 있다. 혈관 벽의 두께 측정은 혈관 질병을 진단할 수 있는 대표적인 지표이다. 그러므로 본 연구는 혈관 벽에서 수신되는 초음파 RF(Radio Frequency) 신호를 wavelet 변환하여 두께를 측정할 수 있는 방법을 제안한다. 시뮬레이션 결과를 토대로 두께가 각각 0.53mm, 1.2mm인 고분자 물질을 가지고 두께측정 실험을 행하였다. 기존의 방법인 주파수 스펙트럼법과 제안한 방법인 wavelet 변환법에 의하여 측정된 평균 두께는 0.53mm인 경우 각각 0.670$\pm$0.168mm(79.10%), 0.448$\pm$0.084mm(84.53%)이고, 1.2mm인 경우 각각 0.962$\pm$0.072mm(80.17%), 1.149$\pm$0.066mm(95.15%)이다. In-vitro 실험을 행하기 위하여 한천, gelatin, SiC 결정을 가지고 두께가 0.85mm인 혈관 유사 시편을 제작하였고, 이 시편으로부터 데이터를 획득하여 이를 제안한 방법으로 두께를 측정하였다. 그 결과 제안한 방법으로 측정된 평균 두께는 0.8008$\pm$0.0154mm(94.22%)이다. 결론적으로 wavelet 변환을 통해서 혈관 벽의 두께를 정밀하게 측정할 수 있는 가능성이 있음을 알 수 있다.

• Korean Journal of Psychosomatic Medicine
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• v.16 no.1
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• pp.17-24
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• 2008

Psychosomatic medicine is also known as consultation-liaison psychiatry. Pediatric consultation-liaison psychiatry is composed of all consultation, liaison, diagnostic, therapeutic support and research activities carried out by psychiatrists and other mental professionals in pediatric ward to provide mental health services to physically ill pediatric patients. As the differences in the basic concepts of disease models between psychiatry (psychosocial model) and pediatrics(biomedical model) exist, active communication between the child psychiatrist and pediatric medical staffs is required. Although the general guidelines are similar, there are specific considerations for consultation in children and adolescents. Much work is still needed to identify empirically supported treatments which are effective for managing a board range of psychosocial difficulties in children and adolescents.

• The Journal of the Korea Contents Association
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• v.9 no.2
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• pp.432-438
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• 2009

In this paper, we evaluated the performance of the automatic classifier applied for the discrimination of acute alcoholic liver injury and chronic liver fibrosis. The classifier uses the discriminant peaks of the preprocessed Raman spectrum as a feature set. In preprocessing step, we subtract baseline and apply Savitzky-Golay smoothing filter which is known to be useful at preserving peaks. After identifying discriminant peaks from the spectra, we carried out the classification experiments using MAP and neural networks. According to the experimental results, the classifier shows the promising results to diagnosis alcoholic liver injury and chronic liver fibrosis. Classification results over 80% means that the peaks used as a feature set is useful for diagnosing liver disease.

• Food Industry And Nutrition
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• v.11 no.3
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• pp.6-11
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• 2006

바이러스성 식중독은 장염을 일으키는 원인 병원체 중 노로바이러스에 의해 흔히 발생하며 이외에도 아스트로바이러스나 로타바이러스에 의한 집단 설사 사례가 국내에서 보고된 바 있다. 노로바이러스는 식중독과 관련하여 특히 오염된 식수와 굴 등 어패류의 생식을 통한 감염 사례가 많이 보고되어 있으나 사람 간 전파도 흔히 일어나는 전염력이 매우 높은 바이러스이다. 국내에서는 1999년 이후 보고가 되고 있으며 최근 집단 급식과 관련된 대형 식중독 사례들이 보고되면서 학교급식이 사회적인 이슈로 대두되고 있다. 2000년 이후 질병관리본부는 바이러스성 설사의 국내 발생현황을 파악하기 위하여 전국의 17개 시도보건환경 연구원과 노로바이러스를 포함한 4종의 바이러스성 장염원인 병원체에 대한 전국적인 실험실 감시체계를 운영한 결과 바이러스성 병원체가 확인된 사례의 약 18%에서 노로바이러스가 검출되었고, 집단설사 사례에서는 대부분 노로바이러스가 원인병원체로 확인되었다. 또한 노로바이러스의 조기 검출을 위해 질병관리본부는 2004년 중 노로바이러스 유전자 검출 kit를 자체적으로 제작하여 이를 전국의 시도 보건환경연구원을 연계한 감시체계에서 적극 활용함으로써 노로바이러스 집단설사사례의 조기 검출이 가능하게 되었고 지역내 노로바이러스 검출율을 높이는데 기여하였다. 국립보건연구원은 2003년과 2006년에 발생한 대규모 노로바이러스 식중독 사례 이외에도 산발적으로 지속적으로 발생하는 사례들을 조기에 탐지하고 국내에서 검출되는 설사바이러스 유전형 분포양상과 새로운 유전자형이나 변이주를 조기에 검출하고자 전국적인 노로바이러스 실험실 감시망을 강화하여 운영하고 있으며, 집단설사 발생시 각 사례의 연관성을 신속하게 분석할 수 있는 실시간 분자역학적 유전자 분석체계를 단계적으로 도입하고 있다. 실험실 감시체계 운영과 함께 집단 식중독 유발 병원체의 효율적인 관리를 위해 질병관리본부는 노로바이러스를 포함한 설사 유발 병원체를 신고대상 병원체로 지정(2006.06.12)하여 병원체 검출시 보고하도록 하고 관련 지침을 마련하였다. 노로바이러스가 지정전염병 병원체로 추가로 지정됨에 따라 집단 사례 및 실험실 감시사업을 통해 검출되는 병원체에 대한 보고가 강화되고 전파 방지와 2차 감염 사례 감소에도 기여할 수 있을 것으로 사료되며 전국의 실험실 감시망을 연결하는 국가 차원의 노로바이러스 실시간 분자역학적 분석체계 도입을 통해 노로바이러스 2차 감염을 줄이고 대규모 집단발병 및 유행의 조기 차단 효과를 가져올 수 있을 것이다.

• Journal of the Korea Convergence Society
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• v.11 no.1
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• pp.327-335
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• 2020

The purpose of this study was to investigate conception of children's hospitalization stress and to make clear concepts, and to use Walker & Avant's concept analysis method. Children's hospitalization stress attributes were derived from physiological changes, individual-environmental interactions, cognitive and psychosocial developmental stage responses, and intrinsic and outward changes due to coping styles. The prerequisites for hospitalization stress of children were disease severity, biological factors, and support system, and the results were hospitalization adaptation, disease and health recovery, improvement of child development, and acquisition of coping skills. In order to solve the prerequisites for Hospitalization stress of children, it is necessary to be aware of the disease and to establish a support system of parent-family. Afterwards, we suggest more qualitative research on the hospitalization stress of children, the development of tools that reflect the characteristics of the hospitalization stress of children, and the development of programs to solve the Hospitalization stress.

• Journal of Science and Technology Studies
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• v.13 no.2
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• pp.137-172
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• 2013

Globally, awareness about obesity is increasing rapidly. In Korea, obesity is recognized as a disease and steps are being taken to treat it. From the health governance point of view, such standardized measures amplify the risk of obesity and thus play an important part in the prevention of the disease. In this context, various obesity treatments act as a medium for the problem-solving process. In recent years, obesity surgery has been viewed as a rational solution to the problem of obesity. In the context of standardization of treatment, Callon's "Process of Translation" in STS theories highlights the importance of the central actor (Obligatory Passage Point; OPP). However, in the case of obesity, it is difficult to identify a single OPP to project different perspectives of an actor's needs. "Lapband surgery" often acts as a "boundary object" in this context. This article assesses this absence of central actors in the process of problem solving through a case study of adoption of Lapband surgery in Korea. Further, we attempt to suggest an analytical framework with a boundary object and multiple translation concepts to aid solving the problem of obesity.

• Journal of the Korea Society for Simulation
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• v.25 no.1
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• pp.29-34
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• 2016

Many researchers have used cohort DB (database) to predict the occurrence of disease or to keep track of disease spread. Cohort DB is Big Data which has simply stored disease and health information as separated DB table sets. To measure the relations between health information, It is necessary to reconstruct cohort DB which follows research purpose. In this paper, XML descriptor, editor has been used to construct ontology-based Big Data cohort DB. Also, we have developed ontology based cohort DB search system to check results of relations between health information. XML editor has used 7 layered Ontology development 101 and OWL API to change cohort DB into ontology-based. Ontology-based cohort DB system can measure the relation of disease and health information and can be used effectively when semantic relations are found. We have developed ontology-based cohort DB search system which can measure the relations between disease and health information. And it is very effective when searched results are semantic relations.

• The Journal of Korean Academy of Prosthodontics
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• v.49 no.4
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• pp.341-345
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• 2011

Genetic association study has been progressed in medicine along with advance in genetic technology. It focused on the individual differences in genotype due to errors occurring during DNA duplication, which can cause vulnerability to specific diseases. Polymorphism defines the varieties in phenotype due to those genetic variations. Polymorphism due to change in one DNA base sequence is called as a Single Nucleotide Polymorphism. In the near future, the evaluation of relative risk to specific disease according to SNP will be essential part of fundamental of medicine for the diagnosis, treatment and prevention. Dental caries and periodontal diseases has been first subject to genetic association study in dentistry and broaden out to other areas like bone formation and resorption. This article presents the current state of genetic association study and its application to dentistry.

• Journal of KIISE:Databases
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• v.34 no.1
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• pp.46-58
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• 2007

Since microarray data acquire tens of thousands of gene expression values simultaneously, they could be very useful in identifying the phenotypes of diseases. However, the results of analyzing several microarray datasets which were independently carried out with the same biological objectives, could turn out to be different. One of the main reasons is attributable to the limited number of samples involved in one microarry experiment. In order to increase the classification accuracy, it is desirable to augment the sample size by integrating and maximizing the use of independently-conducted microarray datasets. In this paper, we propose a novel two-stage approach which firstly integrates individual microarray datasets to overcome the problem caused by limited number of samples, and identifies informative genes, secondly builds a classifier using only the informative genes. The classifier from large samples by integrating independent microarray datasets achieves high accuracy up to 24.19% increase as against other comparison methods, sensitivity, and specificity on independent test sample dataset.