• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.538-541
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• 2009

Increasing of number of people who suffered from long term chronic diseases which required frequent daily health monitoring and body check up in conjunction with the trendy uses of mobile phones and Personal Digital Assistants (PDAs) in various ubiquitous computing had make portable healthcare system a well known application today. A mobile phone based portable healthcare monitoring system with multiple vital signals monitoring ability at real time in WSN and CDMA network is developed. This system carries out real time monitoring and local data analysis process in the mobile phone. Any detection of abnormal health condition and diagnosis at earlier stage will reduce the risk of patient's life. As an extension to the existing model, a pre-diagnosis management system (PDMS) is designed to minimize the time consuming in pre-diagnosis process in the hospital or healthcare center. An alert is sent to the web server at the healthcare center when the patient detects his health is at critical state where the immediate diagnosis is needed. Preparation of diagnosis equipments and arrangement of doctor and nurses at the hospital side can be done earlier before the arrival of patient at the hospital with the help of PDMS. An efficient pre-diagnosis management increases the chances of diseases recovery rate as well.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.11
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• pp.135-146
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• 1997

This paper describes fault diagnosis method in complex system with hierachical structure similar to human body structure. Complex system is divided into unit, item and component. For diagnosing this hierarchical complex system, it is necessary to implement special neural network. Fault diagnosis system can forecast faults in a system and decide from current machine state signal information. Comparing with other diagnosis system for single fault, the developed system deals with multiple fault diagnosis comprising Hierarchical Neural Network(HNN). HNN consists of four level neural network, first level for item fault symptom classification, second level for item fault diagnosis, third level for component symptom classification, forth level for component fault diagnosis. UNIX IPC(Inter Process Communication) is used for implementing HNN wiht multitasking and message transfer between processes in SUN workstation with X-Windows(Motif). We tested HNN at four units, seven items per unit, seven components per item in a complex system. Each one neural newtork operate as a separate process in HNN. The message queue take charge of information exdhange and cooperation between each neural network.

• Journal of Korean Academy of Nursing
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• v.30 no.4
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• pp.1078-1087
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• 2000

The purpose of this study was to develop and to evaluate the Computerized Nursing Diagnosis/ Intervention System for Nutritional and Eliminative Problems for clinical application. Each stage was processed based on the System Development Life Cycle. At the Strategy Planning Stage, valid nursing diagnoses and interventions were chosen. At the System Analysis Stage, a nursing diagnosis and intervention flowchart was drawn up. At the System Design Stage, a system was developed based on the flowchart and named the Nursing Diagnosis/Intervention System. The Nursing Diagnosis/Intervention System consisted of the Patient's Basic Information, Patient's Nursing Process, Nursing Process, and Code Registration. Each element in flowchart was coded and made into a database. The System was used and evaluated. A total of 30 cases were collected. After the application, the nurses evaluated the System using a 5 point Likert scale. Every item was scored at three points or more and 13 out of 17 items were scored at four points or more, thus the Nursing Diagnosis/Intervention System that was developed in this study was regarded as a useful one.

• Journal of Korean Academy of Nursing
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• v.26 no.2
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• pp.281-289
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• 1996

Neural networks have recently attracted considerable attention in the field of classification and other areas. The purpose of this study was to demonstrate an experiment using back-propagation neural network model applied to nursing diagnosis. The network's structure has three layers ; one input layer for representing signs and symptoms and one output layer for nursing diagnosis as well as one hidden layer. The first prototype of a nursing diagnosis system for patients with stomach cancer was developed with 254 nodes for the input layer and 20 nodes for the output layer of 20 nursing diagnoses, by utilizing learning data set collected from 118 patients with stomach cancer. It showed a hitting ratio of .93 when the model was developed with 20,000 times of learning, 6 nodes of hidden layer, 0.5 of momentum and 0.5 of learning coefficient. The system was primarily designed to be an aid in the clinical reasoning process. It was intended to simplify the use of nursing diagnoses for clinical practitioners. In order to validate the developed model, a set of test data from 20 patients with stomach cancer was applied to the diagnosis system. The data for 17 patients were concurrent with the result produced from the nursing diagnosis system which shows the hitting ratio of 85％. Future research is needed to develop a system with more nursing diagnoses and an evaluation process, and to expand the system to be applicable to other groups of patients.

• Nuclear Engineering and Technology
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• v.47 no.2
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• pp.176-186
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• 2015

Pattern classifications have become important tools for fault diagnosis in nuclear power plants (NPP). However, it is often difficult to obtain training data under fault conditions to train a supervised classification model. By contrast, normal plant operating data can be easily made available through increased deployment of supervisory, control, and data acquisition systems. Such data can also be used to train classification models to improve the performance of fault diagnosis scheme. In this paper, a fault diagnosis scheme based on semisupervised classification (SSC) scheme is developed. In this scheme, new measurements collected from the plant are integrated with data observed under fault conditions to train the SSC models. The trained models are subsequently applied to new measurements for fault diagnosis. In comparison with supervised classifiers, the proposed scheme requires significantly fewer data collected under fault conditions to train the classifier. The developed scheme has been validated using different fault scenarios on a desktop NPP simulator as well as on a physical NPP simulator using a graph-based SSC algorithm. All the considered faults have been successfully diagnosed. The results have demonstrated that SSC is a promising tool for fault diagnosis in NPPs.

• Journal of Physiology & Pathology in Korean Medicine
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• v.19 no.6
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• pp.1471-1474
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• 2005

Sasang constitution medicine is to do different treatment accordining to sasang constitution. Therefore, the constitution diagnosis in the Sasang constitution medicine is very important thing. The Process of Sasang constitution diagnosis Is difficult thing, because of consuming much time, making every effort. It is apt to be subjective tendency. So it need to make objective method. The QSCC II (Questionnaire of Sasang Constitution Classification II ) have several problems- can't do diagnosis of Taeyangin, the accuracy rate of Sasang constitution diagnosis is not high (probably 60%), and so on. So, we need the new methods for the Sasang constitution Diagnosis. We will modify the problems of QSCC II. The First is the problems of the study execution process, not-multicenter study, a low data, the absent of Taeyangin cases. So, we have to do the multicenter study. The Second is the problems of a query and the method of statistics analysis. We will modify the problems of self-report Questionnaire. That is the problems of self-report Questionnaire, the lack of objective estimation( body type, personal appearance, etc), the absent of the estimation on typical or non-typical type constitution. We modified the problems of QSCC II. Therefore we made the new self-report Questionnaire for patients. We modified the problems of self-report Questionnaire. Therefore we made the new Constituion diagnosis Questionnaire for doctors. We develop the Questionnaire of two ways for the Sasang constitution Diagnosis. The one is the new self-report Questionnaire for patients. The other is the new Constitution diagnosis Questionnaire for doctors. We have to melt down the Questionnaire of two ways for the Sasang constitution Diagnosis.

• Journal of Physiology & Pathology in Korean Medicine
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• v.24 no.6
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• pp.1111-1116
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• 2010

We in this paper design and implement a traditional korean medicine diagnosis system based on basic ontology. If doctors put the symptoms or tongues or pulses of a patient in the diagnosis system, they can be recommended for the diagnosis results. To support the doctors decision, the diagnosis system make the inference based on the basic ontology and compute the similarity between symptoms of patient and those of ontology. The diagnosis systems also provide the learning mechanism about diagnosis results which save the results in the ontology and reuse them in the next diagnosis. Thus, doctors can share their knowledge for the diagnosis by exchanging their ontology each other. In future, we will expand the knowledge of the basic ontology continuously so that doctors can get the more accurate diagnosis results. We also implement the prescription function and integrate it to the diagnosis system.

• Pediatric Gastroenterology, Hepatology & Nutrition
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• v.11 no.sup1
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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.

• Journal of Veterinary Clinics
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• v.25 no.2
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• pp.85-89
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• 2008

This study assessed the incidence of embryo and fetal loss following early pregnancy diagnosis using ultrasonography in dairy cows. A positive pregnancy was a recognition of the vesicle, embryo or fetus by ultrasonography. Seven hundreds and two pregnancies determined by ultrasonography following artificial insemination were divided into three groups according to the number of days diagnosed pregnant: early A group (27 to 40 days, n = 143), early B group (41 to 50 days, n = 172), or standard group (51 to 70 days, n = 387). Following a positive pregnancy diagnosis, embryo or fetal loss included all cows with observed abortions and cows found open after the positive pregnancy diagnosis. The incidence rate of embryo or fetal loss within 7 days after pregnancy diagnosis was 1.4, 0.6 and 0.3% for the early A, early B, and standard groups, respectively (P>0.05). The incidence of the embryo or fetal loss during 8 to 30 days after pregnancy diagnosis did not differ (P>0.05) among the early A (0%), early B (1.2%), and standard groups (1.0%). Furthermore, the cumulative incidence of the embryo or fetal loss before calving did not differ (P>0.05) among the early A (9.8%), early B (9.3%), and standard groups (5.9%). These results indicate that early pregnancy diagnosis using ultrasonography does not increase the risk of embryo and fetal loss compared with that of routine pregnancy diagnosis in dairy cows.

• Journal of Cardiovascular Imaging
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• v.31 no.4
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• pp.159-168
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• 2023

BACKGROUND: The gold standard for diagnosis of cardiac tumours is histopathological examination. Cardiovascular magnetic resonance (CMR) is a valuable non-invasive, radiation-free tool for identifying and characterizing cardiac tumours. Our aim is to understand CMR diagnosis of cardiac tumours by distinguishing benign vs. malignant tumours compared to the gold standard. METHODS: A systematic search was performed in the PubMed, Web of Science, and Scopus databases up to December 2022, and the results were reviewed by 2 independent investigators. Studies reporting CMR diagnosis were included in a meta-analysis, and pooled measures were obtained. The risk of bias was assessed using the Quality Assessment Tools from the National Institutes of Health. RESULTS: A total of 2,321 results was obtained; 10 studies were eligible, including one identified by citation search. Eight studies were included in the meta-analysis, which presented a pooled sensitivity of 93% and specificity of 94%, a diagnostic odds ratio of 185, and an area under the curve of 0.98 for CMR diagnosis of benign vs. malignant tumours. Additionally, 4 studies evaluated whether CMR diagnosis of cardiac tumours matched specific histopathological subtypes, with 73.6% achieving the correct diagnosis. CONCLUSIONS: To the best of our knowledge, this is the first published systematic review on CMR diagnosis of cardiac tumours. Compared to histopathological results, the ability to discriminate benign from malignant tumours was good but not outstanding. However, significant heterogeneity may have had an impact on our findings.