• Annals of Clinical Neurophysiology
• /
• v.24 no.1
• /
• pp.7-16
• /
• 2022

Background: There is inadequate information on the validation of diabetic microvascular complications in the Korean National Health Insurance Service data set. We aimed to validate the diagnostic algorithms regarding the nephropathy, neuropathy, and retinopathy of diabetes. Methods: From various secondary and tertiary medical centers, we selected 6,493 patients aged ≥ 40 years who were diagnosed with diabetic microvascular complications more than once based on codes in the 10th version of the International Classification of Diseases (ICD-10). During 2019 and 2020, we randomly selected the diagnoses of 200 patients, 100 from each of two hospitals. The positive predictive value (PPV), negative predictive value, error rate, sensitivity, and specificity were determined for each diabetic microvascular complication according to the ICD-10 codes, laboratory findings, diagnostic studies, and treatment procedure codes. Results: Among the 200 patients who visited the hospital more than once and had the diagnostic codes of diabetic microvascular complications, 142, 110, and 154 patients were confirmed to have the gold standard of diabetic nephropathy (PPV, 71.0%), diabetic neuropathy (PPV, 55.0%), and diabetic retinopathy (PPV, 77.0%), respectively. The PPV and specificity of diabetic nephropathy (PPV, 71.0-81.4%; specificity, 10.3-53.4%), diabetic neuropathy (PPV, 55.0-81.3%; specificity, 66.7-76.7%) and diabetic retinopathy (PPV, 77.0-96.6%; specificity, 2.2-89.1%) increased after combining them with the laboratory findings, diagnostic studies, and treatment procedures codes. These change trends were observed similarly for both hospitals. Conclusions: Defining diabetic microvascular complications using ICD-10 codes and their related examination codes may be a feasible method for studying diabetic complications.

• Korean Journal of Transplantation
• /
• v.31 no.4
• /
• pp.170-176
• /
• 2017

We need to establish an informative guideline to increase inter-institutional and inter-observer reproducibility of renal transplant diagnosis, and to improve the diagnostic ability of pathologists in Korea. A first nation-wide survey for renal transplant pathology was conducted by Renal Pathology Study Group of the Korean Society of Pathologists in 2016, to provide the continued excellence in the transplantation pathology laboratory, and to improve the diagnostic ability for the best treatment of transplant patients. This survey revealed the significant variations in scale, work load and biopsy indications for the renal transplant pathology in various institutions in Korea. The Banff classification were used by all institutions for the diagnosis of renal transplant pathology, but different formats were used: most institutions (70%) used the "2013 Banff classification" while the others were using "2007 Banff classification" (20%) or even older formats. In daily diagnostic practice of the renal allografts, difficulties that pathologists encounter were quite diverse due to different environments they work in. Most respondents agreed that standardized diagnostic practice guidelines, regular education on renal transplant pathology and convenient ways of consultation are further needed. We are currently working toward the enhancement of the expertise of renal pathologists and to increase inter-institutional and inter-observer reproducibility by 1) development of a set of virtual slides of renal allograft biopsies for the training, 2) validation and gathering expert's consensus on the core variables of rejection diagnosis by using virtual slides, and 3) continued education by the developed virtual slide atlas.

• Korean Journal of Clinical Laboratory Science
• /
• v.54 no.2
• /
• pp.79-94
• /
• 2022

Due to the highly contagious nature and severity of the respiratory diseases caused by COVID-19, economical and accurate tests are required to better monitor and prevent the spread of this contagion. As the structural and molecular properties of SARS-CoV-2 were being revealed during the early stage of the COVID-19 pandemic, many manufacturers of COVID-19 diagnostic kits actively invested in the design, development, validation, verification, and implementation of diagnostic tests. Currently, diagnostic tests for SARS-CoV-2 are the most widely used and validated techniques for rapid antigen, and immuno-serological assays for specific IgG and IgM antibody tests and molecular diagnostic tests. Molecular diagnostic assays are the gold standard for direct detection of viral RNA in individuals suspected to be infected with SARS-CoV-2. Antibody-based serological tests are indirect tests applied to determine COVID-19 prevalence in the community and identify individuals who have obtained immunity. In the future, it is necessary to explore technical problems encountered in the early stages of global or regional outbreaks of pandemics and provide future directions for better diagnostic tests. This article evaluates the commercially available and FDA-approved molecular and immunological diagnostic assays and analyzes their performance characteristics.

• BMB Reports
• /
• v.38 no.5
• /
• pp.555-562
• /
• 2005

Single nucleotide polymorphisms (SNPs) are becoming the most common type of markers used in genetic analysis. In the present report a SNP has been chosen to test the applicability of Real Time PCR to discriminate and quantify SNPs alleles on DNA pools. Amplification Refractory Mutation System (ARMS) and Mismatch Amplification Mutation Assay (MAMA) has been applied. Each assay has been pre-validated testing specificity and performances (linearity, PCR efficiency, interference limit, limit of detection, limit of quantification, precision and accuracy). Both the approaches achieve a precise and accurate estimation of the allele frequencies on pooled DNA samples in the range from 5% to 95% and don't require standard curves or calibrators. The lowest measurement that could be significantly distinguished from the background noise has been determined around the 1% for both the approaches, allowing to extend the range of quantifications from 1% to 99%. Furthermore applicability of Real Time PCR assays for general diagnostic purposes is discussed.

• Nuclear Engineering and Technology
• /
• v.50 no.4
• /
• pp.532-541
• /
• 2018

Decision support systems are a key focus of research on developing control rooms to aid operators in making reliable decisions and reducing incidents caused by human errors. For this purpose, models of complex systems can be developed to diagnose causes or consequences for specific alarms. Models applied in safety systems of complex and safety-critical systems require rigorous and reliable model building and testing. Multilevel flow modeling is a qualitative and discrete method for diagnosing faults and has previously only been validated by subjective and qualitative means. To ensure reliability during operation, this work aims to synthesize a procedure to measure model performance according to diagnostic requirements. A simple procedure is proposed for validating and evaluating the concept of multilevel flow modeling. For this purpose, expert statements, dynamic process simulations, and pilot plant experiments are used for validation of simple multilevel flow modeling models of a hydrocyclone unit for oil removal from produced water.

• BMB Reports
• /
• v.41 no.10
• /
• pp.685-692
• /
• 2008

Colorectal cancer (CRC) is the third most common malignancy in the world. Because CRC develops slowly from removable precancerous lesions, detection of the disease at an early stage during regular health examinations can reduce both the incidence and mortality of the disease. Although sigmoidoscopy offers significant improvements in the detection rate of CRC, its diagnostic value is limited by its high costs and inconvenience. Therefore, there is a compelling need for the identification of noninvasive biomarkers that can enable earlier detection of CRC. Accordingly, many validation studies have been conducted to evaluate genetic, epigenetic or protein markers that can be detected in the stool or in serum. Currently, the fecal-occult blood test is the most widely used method of screening for CRC. However, advances in genomics and proteomics combined with developments in other relevant fields will lead to the discovery of novel non invasive biomarkers whose usefulness will be tested in larger validation studies. Here, non-invasive molecular biomarkers that are currently used in clinical settings and have the potential for use as CRC biomarkers are discussed.

• Journal of the Korean Society for Aviation and Aeronautics
• /
• v.16 no.2
• /
• pp.1-11
• /
• 2008

Increasing demand for improved reliability and survivability of mission-critical systems is driving the development of health monitoring and Automated Contingency Management (ACM) systems. An ACM system is expected to adapt autonomously to fault conditions with the goal of still achieving mission objectives by allowing some degradation in system performance within permissible limits. ACM performance depends on supporting technologies like sensors and anomaly detection, diagnostic/prognostic and reasoning algorithms. This paper presents the development of a generic prototype test bench software framework for developing and validating ACM systems for advanced propulsion systems called the Propulsion ACM (PACM) Test Bench. The architecture has been implemented for a Monopropellant Propulsion System (MPS) to demonstrate the validity of the approach. A Simulink model of the MPS has been developed along with a fault injection module. It has been shown that the ACM system is capable of mitigating the failures by searching for an optimal strategy. Furthermore, the concepts of Validation and Verification (V&V) of such systems are introduced with relevant examples.

• International Journal of Naval Architecture and Ocean Engineering
• /
• v.10 no.5
• /
• pp.617-628
• /
• 2018

Several techniques have been developed in the last years for energy conversion and aeronautic propulsion plants monitoring and diagnostics, to ensure non-stop availability and safety, mainly based on machine learning and pattern recognition methods, which need large databases of measures. This paper aims to describe a simulation based monitoring and diagnostic method to overcome the lack of data. An application on a gas turbine powered frigate is shown. A MATLAB-SIMULINK(R) model of the frigate propulsion system has been used to generate a database of different faulty conditions of the plant. A monitoring and diagnostic system, based on Mahalanobis distance and artificial neural networks have been developed. Experimental data measured during the sea trials have been used for model calibration and validation. Test runs of the procedure have been carried out in a number of simulated degradation cases: in all the considered cases, malfunctions have been successfully detected by the developed model.

• Nuclear Engineering and Technology
• /
• v.49 no.5
• /
• pp.896-904
• /
• 2017

Several Generation IV nuclear reactor concepts have goals for optimizing investment recovery through phased introduction of multiple units on a common site with shared facilities and/or reconfigurable energy conversion systems. Additionally, small modular reactors are suitable for remote deployment to support highly localized microgrids in isolated, underdeveloped regions. The long-term economic viability of these advanced reactor plants depends on significant reductions in plant operations and maintenance costs. To accomplish these goals, intelligent control and diagnostic capabilities are needed to provide nearly autonomous operations with anticipatory maintenance. A nearly autonomous control system should enable automatic operation of a nuclear power plant while adapting to equipment faults and other upsets. It needs to have many intelligent capabilities, such as diagnosis, simulation, analysis, planning, reconfigurability, self-validation, and decision. These capabilities have been the subject of research for many years, but an autonomous control system for nuclear power generation remains as-yet an unrealized goal. This article describes a functional framework for intelligent, autonomous control that can facilitate the integration of control, diagnostic, and decision-making capabilities to satisfy the operational and performance goals of power plants based on multimodular advanced reactors.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
• /
• v.30 no.1
• /
• pp.9-16
• /
• 2019

Objectives: The purpose of this study was to analyze the discriminant validity and the clinical cut off scores of the Child Behavior Checklist 1.5-5 (CBCL 1.5-5) in the diagnosis of autism spectrum disorder (ASD) and non-ASD. Methods: In total, 104 ASD and 441 non-ASD infants were included in the study. T-test, discriminant analysis, receiver operating characteristic (ROC) curve analysis, and odds ratio analysis were performed on the data. Results: The discriminant validity was confirmed by mean differences and discriminant analysis on the subscales of Emotionally reactive, Somatic complaints, Withdrawn, Sleep problems, Attention problems, Aggressive behavior, Internalizing problems, Externalizing problems, and Total problems, along with the Diagnostic and Statistical Manual of Mental Disorders (DSM)-oriented scales between the two groups. ROC analysis showed that the following subscales significantly separated ASD from normal infants: Emotionally reactive, Somatic complaints, Withdrawn, Sleep problems, Attention problems, Aggressive behavior, Internalizing problems, Externalizing problems, Total problems, and DSM pervasive developmental problems. Moreover, the clinical cut off score criteria adopted in the Korean-CBCL 1.5-5 were shown to be valid for the subscales Withdrawn, Internalizing problems, Externalizing problems, Total problems, and DSM pervasive developmental problems. Conclusion: The subscales of Withdrawn, Internalizing problems, Externalizing problems, Total problems, and DSM pervasive developmental problems significantly discriminated infants with ASD.