• Journal of mucopolysaccharidosis and rare diseases
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• 제2권1호
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• pp.19-22
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• 2016

Purpose: Mucolipidosis type II (ML II), also known as I-cell disease is an autosomal recessive inherited disorder of lysosomal enzyme transport caused by a deficiency of the uridine diphosphate (UDP)-N-acetylglucosamine:lysosomal enzyme N-acetylglucosamine-1-phosphotransferase (GlcNAc-phosphotransferase). Clinical manifestations are skeletal abnormalities, mental retardation, cardiac disease, and respiratory complications. A severely and rapidity progressive clinical course leads to death before 10 years of age. Methods/Results: In this study we diagnosed three cases of prenatal ML II in two different at-risk families. We compared two procedures -biochemical analysis and molecular analysis - for the prenatal diagnosis of ML II. Both methods require an invasive procedure to obtain specimens for the diagnosis. Biochemical analysis requires obtaining cell cultures from amniotic fluid for more than two weeks, and would result in a late diagnosis at 19 to 22 weeks of gestation. Molecular genetic testing by direct sequence analysis is usually possible when mutations are confirmed in the proband. Molecular analysis has an advantage in that it can be performed during the first-trimester. Conclusion: Molecular diagnosis is a preferable method when a prompt decision is necessary.

• Tuberculosis and Respiratory Diseases
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• 제57권6호
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• pp.515-521
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• 2004

With the increasing resolution of modern CT scanners, analysis of the larger numbers of images acquired in a lung screening exam or diagnostic study is necessary, which also needs high accuracy and reproducibility. Recent developments in the computerized analysis of medical images are expected to aid radiologists and other healthcare professional in various diagnostic tasks of medical image interpretation. This article is to provide a brief overview of some of computer-aided diagnosis schemes in chest CT.

• 산업경영시스템학회지
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• 제18권36호
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• pp.61-69
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• 1995

The diagnosis has an very important role in curing dementia. But there was not the effective method to diagnose it until now. In this paper we analyzed the EEG in Alzheimer's disease and normal control groups to differentiated them by nonlinear parameter such as the correlation dimension. And we propose the nonlinear analysis of EEG in Alzheimer's disease as a useful tool of early diagnosis of it.

• 지역사회간호학회지
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• 제12권1호
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• pp.3-21
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• 2001

Nursing diagnosis classification is needed to define nursing phenomena and set up nursing plans. The purpose of this study is to develope common nursing diagnosis by comparing and analysing nursing diagnosis classification systems and assessment tools in home care. The target home care nursing diagnosis classifications and tools are HHCC. NANDA. OMAHA. MDS_HC 2.0. OASIS-Bl. Results of this study are as follows: - The number of components of nursing diagnosis classifications and tools is HHCC 4. NANDA 9. OMAHA 4. MDS_HC2.0 6. OASIS-B1 10. - The number of common nursing diagnosis in home care is summed up 51 which are physical heal th 17. social health 5. psychological health 11. health related behavior 13. environment 3.

• Pediatric Gastroenterology, Hepatology & Nutrition
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• 제11권sup1호
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• pp.72-82
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• 2008

Wilson disease (WD) is an autosomal recessive disorder of copper metabolism that results in accumulation of copper primarily in the liver, the brain and the cornea. Mutations in the WD gene, ATP7B cause failure of copper excretion from hepatocyte into bile and a defective synthesis of ceruloplasmin. More than 370 mutations are now recognized, scattering throughout the ATP7B gene. Since WD has protean clinical presentations, awareness of WD in clinical practice is important for the early diagnosis and prevention of accumulated copper toxicity. None of the laboratory parameters alone allows a definite diagnosis of WD. There are numerous pitfalls in the diagnosis of WD. Low serum ceruloplasmin concentrations, increased 24 hour urinary copper excretion, increased hepatic copper concentrations and the presence of Kayser-Fleischer rings in the cornea are major diagnostic points. A combination of any two of these 4 laboratory findings is strong support for a diagnosis of WD. Molecular methods are now being used to aid diagnosis. Molecular genetic testing has confirmed the diagnosis in individuals in whom the diagnosis is not clearly established biochemically and clinically. Siblings should be screened for WD once an index case has been diagnosed. Discrimination of heterozygotes from asymptomatic patients is essential to avoid inappropriate lifelong therapy for heterozygotes. Genetic testing, either by haplotype analysis or by mutation analysis, is the only reliable tool for differentiating heterozygote carriers from affected asymptomatic patients. Currently, genetic testing is of limited value in the primary diagnosis. However, genetic testing will soon play an essential role in diagnosing WD as rapid advancement of biomedical technology will allow more rapid, easier and less expensive mutation detection.

• 산업경영시스템학회지
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• 제42권4호
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• pp.126-134
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• 2019

Nowadays, since there are so many big data available everywhere, those big data can be used to find useful information to improve design and operation by using various analysis methods such as data mining. Especially if we have event log data that has execution history data of an organization such as case_id, event_time, event (activity), performer, etc., then we can apply process mining to discover the main process model in the organization. Once we can find the main process from process mining, we can utilize it to improve current working environment. In this paper we developed a new method to find a final diagnosis of a patient, who needs several procedures (medical test and examination) to diagnose disease of the patient by using process mining approach. Some patients can be diagnosed by only one procedure, but there are certainly some patients who are very difficult to diagnose and need to take several procedures to find exact disease name. We used 2 million procedure log data and there are 397 thousands patients who took 2 and more procedures to find a final disease. These multi-procedure patients are not frequent case, but it is very critical to prevent wrong diagnosis. From those multi-procedure taken patients, 4 procedures were discovered to be a main process model in the hospital. Using this main process model, we can understand the sequence of procedures in the hospital and furthermore the relationship between diagnosis and corresponding procedures.

• 한국멀티미디어학회논문지
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• 제20권2호
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• pp.134-143
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• 2017

Machine fault diagnosis recovers all the studies that aim to detect automatically faults or damages on machines. Generally, it is very difficult to diagnose a machine fault by conventional methods based on mathematical models because of the complexity of the real world systems and the obvious existence of nonlinear factors. This study develops an automatic machine fault diagnosis system that uses pattern recognition techniques such as principal component analysis (PCA) and artificial neural networks (ANN). The sounds emitted by the operating machine, a drill in this case, are obtained and analyzed for the different operating conditions. The specific machine conditions considered in this research are the undamaged drill and the defected drill with wear. Principal component analysis is first used to reduce the dimensionality of the original sound data. The first principal components are then used as the inputs of a neural network based classifier to separate normal and defected drill sound data. The results show that the proposed PCA-ANN method can be used for the sounds based automated diagnosis system.

• 문화기술의 융합
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• 제10권4호
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• pp.663-668
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• 2024

본 논문에서는 웨이퍼 이송 로봇의 고장 진단에 시간 영역에서의 통계적 분석 방법을 적용하고, 진동 및 토크 신호의 중요 특성을 파악하는 방법을 제안한다. 이를 기반으로 데이터의 차원을 축소하기 위해 주성분 분석을 사용하고, 유클리드 거리와 Hotelling의 T-제곱 통계량을 활용하여 고장 진단 알고리즘을 개발했다. 이 알고리즘은 관측된 데이터에 대해 고장 상태를 분류하는 결정 경계를 형성한다. 속도 파라미터를 고려한 데이터 분류는 진단 정확도를 향상시킴을 확인했다. 이러한 접근 방식은 고장 진단의 정확성과 효율성을 개선하는 데 기여한다.

• 사상체질의학회지
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• 제28권1호
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• pp.1-10
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• 2016

Objectives SCAT (Sasang Constitution Analysis Tool) is a system designed to provide the information needed to diagnose a sasang constitution diagnosis expert diagnosis. In order to determine the sasang constitution diagnosis requires the following four ways. This system provides objective information to the constitution diagnostic expert to collect such information.Methods SCAT was constructed by considering the user UI/UX to be easy to enter information. To provide a state of the subject in Table to make it easier to grasp the information of the subject also in constitution diagnostician.Results Provides objective data for experts to determine the constitutional history of the subject.Conclusions Professionals and ordinary users through the SCAT system can easily access the sasang constitution diagnosis. In the future through the advancement of the SCAT system will improve the user's convenience stability.

• 대한기계학회논문집A
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• 제21권5호
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• pp.835-841
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• 1997

Microscopic examination of the morphology of wear debris is an accepted method for machine condition and fault diagnosis. However wear particle analysis has not been widely accepted in industry because it is dependent on expert interpretation of particle morphology and subjective assessment criteria. This paper was undertaken to analyze the morphology of wear debris for machine condition diagnosis of the lubricated moving surfaces by image processing and analysis. The lubricating wear test was performed under different sliding conditions using a wear test device made in our laboratory and wear testing specimen of the pin-on-disk-type was rubbed in paraffine series base oil. In order to describe characteristics of debris of various shape and size, four shape parameters (50% volumetric diameter, aspect, roundness and reflectivity) have been developed and outlined in the paper. A system using such techniques promises to obviate the need for subjective, human interpretation of particle morphology in machine condition monitoring, thus to overcome many of the difficulties in current methods and to facilitate wider use of wear particle analysis in machine condition monitoring.