• Journal of Applied Reliability
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• v.8 no.2
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• pp.101-111
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• 2008

Good diagnostics improves both the safety and system unavailability of digital safety systems. The measure of a diagnostic capability is called the Coverage Factor. Because the Failure Modes, Effects and Diagnostic Analysis (FMEDA) provides information on the failure rates and failure mode distributions necessary to calculate a diagnostic coverage factor for a component, the FMEDA can be used as a useful tool to calculate it. Through performing FMEDA on a digital signal processor (DSP) board used in a digital safety system, it is shown that some components of the DSP board can be replaced or improved to satisfy the required diagnostic coverage. That is, the FMEDA can serve as a useful verification tool to design a diagnostic capability for the DSP board.

• Korean Journal of Radiology
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• v.21 no.1
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• pp.25-32
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• 2020

Objective: To comparatively evaluate the scan coverage and diagnostic performance of the two-view scan technique (2-VST) of the automated breast ultrasound system (ABUS) versus the conventional three-view scan technique (3-VST) in women with small breasts. Materials and Methods: Between March 2016 and May 2017, 136 asymptomatic women with small breasts (bra cup size A) suitable for 2-VST were enrolled. Subsequently, 272 breasts were subjected to bilateral whole-breast ultrasound examinations using ABUS and the hand-held ultrasound system (HHUS). During ABUS image acquisition, one breast was scanned with 2-VST, while the other breast was scanned with 3-VST. In each breast, the breast coverage and visibility of the HHUS detected lesions on ABUS were assessed. The sensitivity and specificity of ABUS were compared between 2-VST and 3-VST. Results: Among 136 breasts, eight cases of breast cancer were detected by 2-VST, and 10 cases of breast cancer were detected by 3-VST. The breast coverage was satisfactory in 94.1% and 91.9% of cases under 2-VST and 3-VST, respectively (p = 0.318). All HHUS-detected lesions were visible on the ABUS images regardless of the scan technique. The sensitivities and specificities were similar between 2-VST and 3-VST (100% [8/8] vs. 100% [10/10], and 97.7% [125/128] vs. 95.2% [120/126], respectively), with no significant difference (p > 0.05). Conclusion: 2-VST of ABUS achieved comparable scan coverage and diagnostic performance to that of conventional 3-VST in women with small breasts.

• Korean Journal of Radiology
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• v.22 no.3
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• pp.442-453
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• 2021

Artificial intelligence (AI) will likely affect various fields of medicine. This article aims to explain the fundamental principles of clinical validation, device approval, and insurance coverage decisions of AI algorithms for medical diagnosis and prediction. Discrimination accuracy of AI algorithms is often evaluated with the Dice similarity coefficient, sensitivity, specificity, and traditional or free-response receiver operating characteristic curves. Calibration accuracy should also be assessed, especially for algorithms that provide probabilities to users. As current AI algorithms have limited generalizability to real-world practice, clinical validation of AI should put it to proper external testing and assisting roles. External testing could adopt diagnostic case-control or diagnostic cohort designs. A diagnostic case-control study evaluates the technical validity/accuracy of AI while the latter tests the clinical validity/accuracy of AI in samples representing target patients in real-world clinical scenarios. Ultimate clinical validation of AI requires evaluations of its impact on patient outcomes, referred to as clinical utility, and for which randomized clinical trials are ideal. Device approval of AI is typically granted with proof of technical validity/accuracy and thus does not intend to directly indicate if AI is beneficial for patient care or if it improves patient outcomes. Neither can it categorically address the issue of limited generalizability of AI. After achieving device approval, it is up to medical professionals to determine if the approved AI algorithms are beneficial for real-world patient care. Insurance coverage decisions generally require a demonstration of clinical utility that the use of AI has improved patient outcomes.

• Korean Journal of Radiology
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• v.25 no.6
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• pp.505-507
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• 2024

• Korean Journal of Radiology
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• v.25 no.8
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• pp.691-694
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• 2024

• Journal of Periodontal and Implant Science
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• v.44 no.6
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• pp.300-306
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• 2014

Purpose: A laterally positioned flap (LPF) combined with a subepithelial connective tissue graft (SCTG) is one of the conventional approaches for resolving gingival recession defects, with the advantages of flap flexibility and extended coverage of the tissue graft. However, thus far, evidence is lacking for the use of this technique for the treatment of advanced gingival recession defects. This report discusses three Miller class III cases with interproximal bone loss and wide and deep defects treated with a combination procedure of a modified laterally positioned flap (mLPF) and SCTG. Methods: mLPF combined with SCTG was performed for each case. The defect size and the degree of hypersensitivity at baseline and the final appointment in each case were documented. Results: The three cases had a mean initial defect of $7.7{\pm}1.5mm$ and a mean residual defect of $1.7{\pm}1mm$ at the 6-, 3-, and 36-month follow-up, respectively, after the root coverage surgery. The symptom of hypersensitivity was improved, and the patients were satisfied with the clinical outcomes. Conclusions: The results demonstrated that the combination of mLPF with SCTG is promising for treating these advanced cases with respect to obtaining the expected root coverage with the gingival tissue.

• Communications for Statistical Applications and Methods
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• v.17 no.2
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• pp.275-292
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• 2010

Receiver operating characteristic(ROC) curves can be used to assess the accuracy of tests measured on ordinal or continuous scales. The most commonly used measure for the overall diagnostic accuracy of diagnostic tests is the area under the ROC curve(AUC). When two ROC curves are constructed based on two tests performed on the same individuals, statistical analysis on differences between AUCs must take into account the correlated nature of the data. This article focuses on confidence interval estimation of the difference between paired AUCs. We compare nonparametric, maximum likelihood, bootstrap and generalized pivotal quantity methods, and conduct a monte carlo simulation to investigate the probability coverage and expected length of the four methods.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.36C no.9
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• pp.44-53
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• 1999

Generating diagnostic test patterns for combinational circuits remain to be a very difficult problem. For example, ISCAS85 c7552 benchmark circuit has 100 million fault pairs, Thus, we need more sophisticated algorithm to get more information. A new diagnostic algorithm for test pattern generation is suggested and implemented in this paper. DIATEST algorithm based on PODEM is also implemented for comparison to the new algorithm. These two algorithms have been applied to ISCAS85 benchmark circuits. Experimental results show that (1) both algorithms achieve fault pair coverage over 99%, (2) total test length of the new algorithm is much shorter than that of DIATEST, and (3) the new algorithm gives much more information used for making diagnostic dictionary, diagnostic decision tree or diagnostic test system despite DIATEST is faster than the new algorithm.

• IE interfaces
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• v.25 no.4
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• pp.422-430
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• 2012

In this article, we introduced the estimation method by 'Safety Integrity Level'(SIL) for the criterion of safety assurance and performed a case study on a flame scanner. SIL requires probabilistic evaluation of each set of equipment used to reduce risk in a safety related system. FMEDA(Failure Modes, Effects and Diagnostic Analysis) method is widely used to evaluate the safety levels and provides information on the failure rates and failure mode distributions necessary to calculate a diagnostic coverage factor for a part or a component. Basically, two parameters resulting from FMEDA are used for SIL classification of the device : SFF(Safe Failure Fraction) and PFD(Probability of Failure on Demand). In this case study, it is concluded that the flame scanner is designed to fulfill the condition of SIL 3 in the aspect of SFF and PFD.

• Tuberculosis and Respiratory Diseases
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• v.55 no.3
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• pp.239-249
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• 2003

Multi-detector row CT (MDCT) provides faster speed, longer coverage in conjunction with thin slices, improved spatial resolution, and ability to produce high quality muliplanar and three-dimensional (3D) images. MDCT has revolutionized the non-invasive evaluation of the central airways. Simultaneous display of axial, multiplanar, and 3D images raises precision and accuracy of the radiologic diagnosis of central airway disease. This article introduces central airway imaging with MDCT emphasizing on the emerging role of multiplanar and 3D reconstruction.