• Communications for Statistical Applications and Methods
• /
• v.2 no.2
• /
• pp.296-302
• /
• 1995

When heteroscedasticity occurs in random effects linear model, the error variance may depend on the values of one or more of the explanatory variables or on other relevant quantities such as time or spatial ordering. In this paper we derive a score test as a diagnostic tool for detecting non-constant error variance in random effefts linear model based on the model expansion on error variance. This score test is compared to loglikelihood ratio test.

• Journal of the Korean Statistical Society
• /
• v.29 no.2
• /
• pp.231-245
• /
• 2000

This paper considers a linear regression model with space and time data in where the disturbances follow spatially correlated error components. We provide the best linear unbiased predictor for the one way error components. We provide the best linear unbiased predictor for the one way error component model with spatial autocorrelation. Further, we derive two diagnostic test statistics for the assessment of model specification due to spatial dependence and random effects as an application of the Lagrange Multiplier principle.

• Communications for Statistical Applications and Methods
• /
• v.7 no.3
• /
• pp.677-686
• /
• 2000

Outliers may occur with respect to any of the random components in mixed linear models. We develop a use of simple, inexpensive updating formulas to consider the effect of case-deletion for mixed linear models. The method described here requires inversions of an n x n matrix, where n is the number of nonempty cells. A numerical example illustrates the use of computational formulas.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
• /
• 1997.11a
• /
• pp.106-108
• /
• 1997

In this paper, the breakdown strength of Pure HDPE(High density polyethylene) films and aged HDPE films were evaluated using 2-parameter Weibull distribution function. The result show that both were fitted 2-parameter Weibull distribution. This method could be used to be the diagnostic tool to evalute the insulation performance and endurance under the multiple stresses.

• Communications for Statistical Applications and Methods
• /
• v.3 no.2
• /
• pp.21-28
• /
• 1996

Collinearities contained in MEM cause the same problems as they do in traditional regression model, so the detection of collinearities is a crucial topic in MEM. One diagnostic was introduced by Carrillo-Gamboa and Gunst, but their method did not work in some cases. Two alternative collinearity diagnostics that provide reasonable measure of collinearities are proposed. Simulation study is performed to compare the small-sample properties of the proposed collinearity diagnostics.

• Journal of Convergence Korean Medicine
• /
• v.6 no.1
• /
• pp.37-42
• /
• 2024

Objectives: This study aims to evaluate the clinical validity of the system by conducting a clinical study to assess the diagnostic agreement between the system and Korean medical doctors. Methods: This study was conducted from September 7, 2023, to December 7, 2023, across five Korean medicine institutions, involving 100 adult participants aged 20-64 who consented to participate. Participants first entered their symptoms into a web-based program, which utilized an AI-based algorithm to diagnose 36 types of pattern differentiation. Subsequently, Korean medical doctors conducted face-to-face diagnoses using the same 36 types. The diagnostic agreement between the system and the doctors' diagnoses was analyzed using descriptive statistical analysis, and the results were expressed as a percentage agreement. Results: Analysis of the diagnostic data from 100 participants revealed that the web-based diagnosis support system identified an average of 7.76±0.79 patterns per patient, while Korean medical doctors identified an average of 7.99±0.10 patterns per patient. The diagnostic agreement between the system and the doctors showed an average of 7.08±1.08 patterns per patient, with an overall diagnostic agreement rate of 88.57±13.31%. Conclusion: This study developed a web-based diagnosis support system for traditional Korean medicine and evaluated its clinical validity by assessing diagnostic agreement. Comparing the diagnoses of the system with those of Korean medical doctors for 100 patients, the system showed an approximately 89% agreement rate with the clinical diagnoses. The system holds potential for aiding Korean medical doctors in pattern differentiation diagnosis in clinical practice.

• Korean Journal of Biological Psychiatry
• /
• v.20 no.3
• /
• pp.63-65
• /
• 2013

The new edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) is published by the American Psychiatric Association. The diagnostic systems for mental disorders have come under criticism for relying on presenting signs and symptoms with the result that they do not adequately reflect relevant neurobiological and behavioral systems. Finally, the National Institute of Mental Health (NIMH) in the United States has suggested the Research Domain Criteria (RDoC) to develop a research classification system based upon dimensions of neurobiology and behavioral aspect. The present review introduces the RDoC as a new reaseach framework.

• The Korean Journal of Cytopathology
• /
• v.2 no.1
• /
• pp.8-19
• /
• 1991

A statistical analysis of the diagnostic value for 244 aspiration biopsy cytology(ABC) among a total 1,043 cases from various sites was performed. ABC, using diagnostic terminology similar to that of a surgical pathology reports, was compared to the final tissue diagnosis. For the entire series, a sensitivity of 91.8%, a specificity of 99.3%, a positive predictive value of 98.9%, a negative predictive value of 94,8%, and an efficacy of the test of 96.3% were shown. There were 8 false negative and 1 false positive diagnosis. The diagnostic accuracy was 89.8%. Those results indicate that the ABC is a considerably highly accurate procedure that should be routinely employed.

• Journal of Korea Multimedia Society
• /
• v.25 no.10
• /
• pp.1512-1523
• /
• 2022

Artificial intelligence application in digital health care has been increasing with its development of artificial intelligence. The convergence of the healthcare industry and information and communication technology makes the diagnosis of diseases more simple and comprehensible. From the perspective of medical services, its practice as an initial test and a reference indicator may become widely applicable. Therefore, analyzing the factors that are the basis for existing diagnosis protocols also helps suggest directions using artificial intelligence beyond previous regression and statistical analyses. This paper conducts essential diagnostic prediction learning based on the analysis of blood cancer factors reported previously. Blood cancer diagnosis predictions based on artificial intelligence contribute to successfully achieve more than 90% accuracy and validation of blood cancer factors as an alternative auxiliary approach.

• The Journal of Korean Society for School & Community Health Education
• /
• v.19 no.3
• /
• pp.1-14
• /
• 2018

Objectives: The purpose of this study was to investigate the prevalence of metabolic syndrome and to find related factors according to the number of metabolic syndrome diagnostic components in Korean adolescents. Methods: The subjects of this study were 469 Korean adolescents aged from 12 to 18 enrolled in the 2016 Korea National Health and Nutrition Examination Survey. Statistical package R 3.4.2 was used for programming to apply diagnostic criterion of adolescent metabolic syndrome and for the analysis of the data such as weighted frequent analysis, weighted mean analysis and complex sampling design logistic regression analysis. Results: For adolescents 12 to 18 years of age, 2.55% had more than 2(${\geq_-}3$), 9.88% had more than 1(${\geq_-}2$) and 33.17% had more than 0(${\geq_-}1$) metabolic syndrome diagnostic components. It has been found that risk factors for no less than 2 metabolic syndrome diagnostic components were higher body mass index and higher stress, and risk factors for no less than 1 were higher body mass index, younger teenager and female. Conclusion: Obesity is the primary risk factor for the development of adolescent metabolic syndrome. Female or younger teenager are more likely to have one or more metabolic syndrome diagnostic components, and higher stress develop to the risk level of having two or more metabolic syndrome diagnostic components. Therefore, it is important to focus on obesity and stress management for the prevention and control of Korean adolescent metabolic syndrome.