• Asia Marketing Journal
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• v.6 no.2
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• pp.55-68
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• 2004

After Nakanishi and Cooper(1982) suggested a way of transforming the complicated nonlinear MCI model into a simple linear form, the application of MCI model has been increased. However, the use of MCI model in Korea is quite limited. The goal of this paper is to demonstrate the practical application of MCI(Multiplicative Competitive Interaction) model to a consumer goods industry. MCI model is a form of the attraction model explaining the relation between marketing mix variables and market share. In this study, multiple sources of empirical data are incorporated in the model formulation stage. In the estimation process, the equity estimation is applied to solve the possible multi-collinearity problem among marketing mix variables. Results from the fitted model suggest meaningful managerial implications for the management of brand equity and the allocation of resources among marketing mix variables.

• Journal of Convergence for Information Technology
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• v.9 no.8
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• pp.248-253
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• 2019

Early diagnosis of mild cognitive impairment (MCI) can reduce the incidence of dementia. This study developed the MCI prediction model for the elderly in Korea. The subjects of this study were 3,240 elderly (1,502 men, 1,738 women) aged 65 and over who participated in the Korean Longitudinal Survey of Aging (KLoSA) in 2012. Outcome variables were defined as MCI prevalence. Explanatory variables were age, marital status, education level, income level, smoking, drinking, regular exercise more than once a week, average participation time of social activities, subjective health, hypertension, diabetes Respectively. The prediction model was developed using Restricted Boltzmann Machine (RBM) neural network. As a result, age, sex, final education, subjective health, marital status, income level, smoking, drinking, regular exercise were significant predictors of MCI prediction model of rural elderly people in Korea using RBM neural network. Based on these results, it is required to develop a customized dementia prevention program considering the characteristics of high risk group of MCI.

• Journal of the Korea Convergence Society
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• v.11 no.6
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• pp.203-208
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• 2020

This study examined whether Mild Cognitive Impairment (MCI) is related to the reduction of specific memory among linguistic memory and visuospatial memory, and to identify the most predictive index for discriminating MCI from normal elderly. The subjects were analyzed for 189 elderly (103 healthy elderly, 86 MCI). The verbal memory was used by the Seoul Verbal Learning Test. visuospatial memory was measured using the Rey Complex Figure Test. As a result of multiple logistic regression, verbal memory and visuospatial memory showed significant predictive performance in discriminating MCI from normal elderly. On the other hand, when all the confounding variables were corrected, including the results of each memory test, the predictive power was significant in distinguishing MCI from normal aging only in the immediate recall of verbal memory, and the predictive power was not significant in the immediate recall of visuospatial memory. This result suggests that delayed recall of visuospatial memory and immediate recall of verbal memory are the best combinations to discriminate memory ability of MCI.

• Journal of Korean Academy of Nursing
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• v.50 no.2
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• pp.191-199
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• 2020

Purpose: The purpose of this study was to compare sociodemographic characteristics of a normal cognitive group and mild cognitive impairment group, and establish prediction models of Mild Cognitive Impairment (MCI). Methods: This study was a secondary data analysis research using data from "the 4th Korea Longitudinal Study of Ageing" of the Korea Employment Information Service. A total of 6,405 individuals, including 1,329 individuals with MCI and 5,076 individuals with normal cognitive abilities, were part of the study. Based on the panel survey items, the research used 28 variables. The methods of analysis included a χ²-test, logistic regression analysis, decision tree analysis, predicted error rate, and an ROC curve calculated using SPSS 23.0 and SAS 13.2. Results: In the MCI group, the mean age was 71.4 and 65.8% of the participants was women. There were statistically significant differences in gender, age, and education in both groups. Predictors of MCI determined by using a logistic regression analysis were gender, age, education, instrumental activity of daily living (IADL), perceived health status, participation group, cultural activities, and life satisfaction. Decision tree analysis of predictors of MCI identified education, age, life satisfaction, and IADL as predictors. Conclusion: The accuracy of logistic regression model for MCI is slightly higher than that of decision tree model. The implementation of the prediction model for MCI established in this study may be utilized to identify middle-aged and elderly people with risks of MCI. Therefore, this study may contribute to the prevention and reduction of dementia.

• Journal of Oriental Neuropsychiatry
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• v.34 no.4
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• pp.359-368
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• 2023

Objectives: This study aims to establish a Korean medicine doctor's range of services in the dementia relief primary care system based on the previously developed dementia clinical practice guidelines (CPGs). Developing a dementia relief primary care Clinical Pathway (CP) can aid clinically when the Korean medicine primary care doctor conducts treatment. Methods: We analyzed Dementia Korean Medicine Primary Care Model Data and then applied CP Methodology to develop the configuration of the Korean Medicine Primary Care Model. For patients with Alzheimer's dementia (AD), vascular dementia (VD), and mild cognitive impairment (MCI), the Korean Medicine Primary Care Model focuses on improving cognitive function, everyday living abilities and easing symptoms through interventions described in CPGs. The contents of the draft model later include references to already-existing CPs. Results: The study sites were chosen as Korean medical clinics connected to primary care physicians in the dementia-friendly model. The CP used a time task matrix version to arrange the clinical chronology, which included all examinations, diagnoses, and treatment procedures, from the initial appointment to follow-ups and the end of therapy. Conclusions: It anticipates that Korean primary care doctors familiar with dementia can use the offered therapies for the first time by creating the dementia Korean medicine primary care model in this study. This is expected to maximize the range of medical services provided by Korean medicine and improve the standard of medical treatment.

• Journal of the Korean Society of Radiology
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• v.84 no.3
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• pp.638-652
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• 2023

Purpose To investigate the MRI markers for the prediction of amyloid β (Aβ)-positivity in mild cognitive impairment (MCI) and Alzheimer's disease (AD), and to evaluate the differences in MRI markers between Aβ-positive (Aβ [+]) and -negative groups using the machine learning (ML) method. Materials and Methods This study included 139 patients with MCI and AD who underwent amyloid PET-CT and brain MRI. Patients were divided into Aβ (+) (n = 84) and Aβ-negative (n = 55) groups. Visual analysis was performed with the Fazekas scale of white matter hyperintensity (WMH) and cerebral microbleeds (CMB) scores. The WMH volume and regional brain volume were quantitatively measured. The multivariable logistic regression and ML using support vector machine, and logistic regression were used to identify the best MRI predictors of Aβ-positivity. Results The Fazekas scale of WMH (p = 0.02) and CMB scores (p = 0.04) were higher in Aβ (+). The volumes of hippocampus, entorhinal cortex, and precuneus were smaller in Aβ (+) (p < 0.05). The third ventricle volume was larger in Aβ (+) (p = 0.002). The logistic regression of ML showed a good accuracy (81.1%) with mini-mental state examination (MMSE) and regional brain volumes. Conclusion The application of ML using the MMSE, third ventricle, and hippocampal volume is helpful in predicting Aβ-positivity with a good accuracy.