• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2008.04a
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• pp.416-419
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• 2008

In order to ensure the safety, the performance evaluation of the safety-related components in a nuclear power plant such as air-operated valves. In this paper, the diagnostic system(MOVIDS $A^+$) for the performance of air-operated valves was developed. For this purpose, the characteristics of their operation and the methods of the diagnostic tests were reviewed. The setup and diagnostic functions of the system were mentioned. Its applicability was validated through the diagnostic tests of air-operated valves in nuclear power plants. This diagnostic system is now applied in nuclear power plants for performance tests.

• Journal of Veterinary Clinics
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• v.32 no.4
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• pp.319-323
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• 2015

The performance of diagnostic test accuracy is usually summarized by a variety of statistics such as sensitivity, specificity, predictive value, likelihood ratio, and kappa. These indices are most commonly presented when evaluations of competing diagnostic tests are reported, and it is of utmost importance to compare the accuracies of diagnostic tests to decide on the best available test for certain medical disorder. However, it is important to emphasize that specific point values of these indices are merely estimates. If parameter estimates are reported without a measure of uncertainty (precision), knowledgeable readers cannot know the range within which the true values of the indices are likely to lie. Therefore, when evaluations of diagnostic accuracy are reported the precision of estimates should be stated in parallel. To reflect the precision of any estimate of a diagnostic performance characteristic or of the difference between performance characteristics, the computation of confidential interval (CI), an indicator of precision, is widely used in medical literatures in that CIs are more informative to interpret test results than the simple point estimates. The majority of peer-reviewed journals usually require CIs to be specified for descriptive estimates, whereas domestic veterinary journals seem less vigilant on this issues. This paper describes how to calculate the indices and associated CIs using practical examples when assessing diagnostic test performance.

• Journal of Korean Academy of Oral and Maxillofacial Radiology
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• v.28 no.1
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• pp.37-46
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• 1998

The purpose of this study was to evaluate the diagnostic performance of the senior dental students for the proximal dental caries on intraoral radiographs and to compare it with the dental hospital residents, the reference group. It was also investigated the diagnostic performance according to the carious lesion depth. Thirty-five intraoral periapical and bitewing radiographs with 213 proximal surfaces included in this study were selected from the dental patients at Chonnam National University Hospital. The observers were 181 senior dental students from 5 dental schools and 40 dentists who were second year resident from 5 dental hospitals. They were asked to evaluate the presence or the absence of the proximal dental caries. The results were as follows: 1. The mean of the hitting rate for the overall observers was 184.51 surfaces and the diagnostic accuracy was 86.62％. 2. The diagnostic performance of the sound proximal tooth surfaces was very high, i.e., 91.5％ true negative rate and 8.5％ false positive rate. 3. The diagnostic performance of the dentist group was higher than the student group(P<0.05). 4. The proximal dental caries perceptibility increased as the lesion depth increased significantly(P<0.001) except no difference between the carious lesion depth III and IV (P>0.001).

• International Journal of Aeronautical and Space Sciences
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• v.10 no.2
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• pp.34-42
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• 2009

Gas turbine performance diagnostics is a method for detecting, isolating and quantifying faults in gas turbine gas path components. On-line precise fault diagnosis can promote greatly reliability and availability of gas turbine in real time operation. This work proposes a GUI-type on-line diagnostic program using SIMULINK and Fuzzy-Neuro algorithms for a helicopter turboshaft engine. During development of the diagnostic program, a look-up table type base performance module are used for reducing computer calculating time and a signal generation module for simulating real time performance data. This program is composed of the on-line condition monitoring program to monitor on-line measuring performance condition, the fuzzy inference system to isolate the faults from measuring data and the neural network to quantify the isolated faults. Evaluation of the proposed on-line diagnostic program is performed through application to the helicopter engine health monitoring.

• Korean Journal of Veterinary Research
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• v.49 no.2
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• pp.121-125
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• 2009

Paratuberculosis caused by Mycobacterium avium subspecies paratuberculosis (Mpt) is a chronic infectious enteric disease with deleterious impact on the performance in ruminants. In Korea, ELISA has been introduced to detect antibodies to Mpt in individual cattle. However, comparison study with ELISA has not been studied until now. In total, a panel of 899 serum samples obtained from dairy cattle was analyzed with two commercial ELISAs for Mpt to assess the performance. Two ELISAs employed in this study were both licensed worldwide. Two ELISAs applied onto same serum samples showed the moderate agreement (kappa value = 0.60). There was non-significant McNemar test (p = 0.0614) between two ELISA results indicating that each proportion detected by two kits did not differ. In addition, the percent agreement between two ELISA results was turned out to be 96.8% which interpreted excellent reproducibility. It was shown from this study that two ELISAs revealed moderate kappa agreement performance. The implication raised is that when ELISAs as diagnostics are used to detect Mpt in individual cattle, positive reaction by either ELISA should be interpreted as serologically Mpt positive due to presumed low sensitivity of ELISAs and their test agreement being less than 100%.

• Journal of Veterinary Clinics
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• v.33 no.2
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• pp.97-101
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• 2016

In the field of clinical medicine, diagnostic accuracy studies refer to the degree of agreement between the index test and the reference standard for the discriminatory ability to identify a target disorder of interest in a patient. The receiver operating characteristic (ROC) curve offers a graphical display the trade-off between sensitivity and specificity at each cutoff for a diagnostic test and is useful in assigning the best cutoff for clinical use. In this end, the ROC curve analysis is a useful tool for estimating and comparing the accuracy of competing diagnostic tests. This paper reviews briefly the measures of diagnostic accuracy such as sensitivity, specificity, and area under the ROC curve (AUC) that is a summary measure for diagnostic accuracy across the spectrum of test results. In addition, the methods of creating an ROC curve in single diagnostic test with five-category discrete scale for disease classification from healthy individuals, meaningful interpretation of the AUC, and the applications of ROC methodology in clinical medicine to determine the optimal cutoff values have been discussed using a hypothetical example as an illustration.

• Nuclear Medicine and Molecular Imaging
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• v.42 no.sup1
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• pp.134-136
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• 2008

Neuroblastoma is the most common extracranial solid tumor in children. In diagnostic assessment of neuroblastoma, $^{18}F-FDG$ PET has been reported to have high diagnostic performance, especially, very high sensitivity in staging, restaging, and assessment of therapeutic efficacy. In comparison with conventional diagnostic imaging modalities including a, bone scan, and MIBG scan, $^{18}F-FDG$ PET showed better diagnostic performance. According to clinical research data hitherto, $^{18}F-FDG$ PET is expected to be an effective diagnostic tool in the management of neuroblastoma.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.28 no.10
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• pp.670-675
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• 2015

Degradation diagnosis of cable is one of major issues for operation and maintenance in overhead distribution power lines. The diagnostic system for overhead power lines is composed of three parts in functional aspect - a travelling unit, a sensing unit and a communication unit. Among them, sensor detects the defects such as corrosion and disconnecting of power lines. Performance of sensor is very important, and besides, the size and structure of sensor is restricted for installation to small and lightweight diagnostic system. This paper suggests an optimal eddy current sensor best suit for small and lightweight diagnostic system in consideration of detecting performance, size and ease of installation and so on. Proposed sensor has been designed by Drum core structure and can be applied to the all domestic overhead power lines regardless of the cross-sectional areas. Also, it is showed that results of mock environmental test are satisfied.

• Journal of Veterinary Clinics
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• v.32 no.1
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• pp.73-77
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• 2015

There has been increasing attention on sample size requirements in peer reviewed medical literatures. Accordingly, a statistically-valid sample size determination has been described for a variety of medical situations including diagnostic test accuracy studies. If the sample is too small, the estimate is too inaccurate to be useful. On the other hand, a very large sample size would yield the estimate with more accurate than required but may be costly and inefficient. Choosing the optimal sample size depends on statistical considerations, such as the desired precision, statistical power, confidence level and prevalence of disease, and non-statistical considerations, such as resources, cost and sample availability. In a previous paper (J Vet Clin 2012; 29: 68-77) we briefly described the statistical theory behind sample size calculations and provided practical methods of calculating sample size in different situations for different research purposes. This review describes how to calculate sample sizes when assessing diagnostic test performance such as sensitivity and specificity alone. Also included in this paper are tables and formulae to help researchers for designing diagnostic test studies and calculating sample size in studies evaluating test performance. For complex studies clinicians are encouraged to consult a statistician to help in the design and analysis for an accurate determination of the sample size.

• Clinical Endoscopy
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• v.57 no.1
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• pp.11-17
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• 2024

Although magnifying endoscopy with narrow-band imaging is the standard diagnostic test for gastric cancer, diagnosing gastric cancer using this technology requires considerable skill. Artificial intelligence has superior image recognition, and its usefulness in endoscopic image diagnosis has been reported in many cases. The diagnostic performance (accuracy, sensitivity, and specificity) of artificial intelligence using magnifying endoscopy with narrow band still images and videos for gastric cancer was higher than that of expert endoscopists, suggesting the usefulness of artificial intelligence in diagnosing gastric cancer. Histological diagnosis of gastric cancer using artificial intelligence is also promising. However, previous studies on the use of artificial intelligence to diagnose gastric cancer were small-scale; thus, large-scale studies are necessary to examine whether a high diagnostic performance can be achieved. In addition, the diagnosis of gastric cancer using artificial intelligence has not yet become widespread in clinical practice, and further research is necessary. Therefore, in the future, artificial intelligence must be further developed as an instrument, and its diagnostic performance is expected to improve with the accumulation of numerous cases nationwide.