• Journal of Preventive Medicine and Public Health
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• v.39 no.3
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• pp.243-248
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• 2006

Objectives: The Quality of Life-Alzheimer's Disease (QOL-AD) scale is a reliable and valid tool for assessing the quality of life (QOL) in the elderly with dementia. This study aimed to develop the Korean version of Quality of Life-Alzheimer's Disease (KQOL-AD) scale for the demented elderly living in the community. Methods: KQOL-AD was administered to two groups: 24 demented elderly and 72 cognitively impaired elderly with no dementia (CIND) who were living in the community Each elderly person and their caregiver rated the elderly QOL. The Korean version of mini-mental state examination (MMSE-K), the clinical dementia rating (CDR), the activities of daily living (ADL), and the neuropsychiatric inventory (NPI) were also assessed. The reliability and validity of the KQOL-AD were examined. Results: In the dementia group, the internal consistency (Cronbach's $\alpha$), the split half and the test-retest reliabilities of the KQOL-AD were excellent. Scores on the KQOL-AD were significantly correlated with the scores of the NPI, but they were not significantly correlated with scores of the MMSE-K, CDR and ADL. In addition, the CIND group showed similar results to the dementia group. Conclusions: KQOL-AD might be a reliable and valid instrument for assessing QOL in the elderly with dementia It could be used as an important outcome measure for research on the demented elderly.

• Journal of Multimedia Information System
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• v.6 no.4
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• pp.209-216
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• 2019

Over the past decade, researchers were able to solve complex medical problems as well as acquire deeper understanding of entire issue due to the availability of machine learning techniques, particularly predictive algorithms and automatic recognition of patterns in medical imaging. In this study, a technique called transfer learning has been utilized to classify Magnetic Resonance (MR) images by a pre-trained Convolutional Neural Network (CNN). Rather than training an entire model from scratch, transfer learning approach uses the CNN model by fine-tuning them, to classify MR images into Alzheimer's disease (AD), mild cognitive impairment (MCI) and normal control (NC). The performance of this method has been evaluated over Alzheimer's Disease Neuroimaging (ADNI) dataset by changing the learning rate of the model. Moreover, in this study, in order to demonstrate the transfer learning approach we utilize different pre-trained deep learning models such as GoogLeNet, VGG-16, AlexNet and ResNet-18, and compare their efficiency to classify AD. The overall classification accuracy resulted by GoogLeNet for training and testing was 99.84% and 98.25% respectively, which was exceptionally more than other models training and testing accuracies.

• Korean Journal of Adult Nursing
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• v.24 no.4
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• pp.398-405
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• 2012

Purpose: The purpose of this study was to develop spaced retrieval training as a nursing intervention for patients having an mild alzheimer's disease and to determine the effects of the program on their memory and cognitive function across training sessions. Methods: A non-equivalent control group pre test-post test design was used in this study. Participants were recruited from a local community: 14 patients were allocated into experimental group and 12 patients were allocated into control group. The experimental group was asked to participate in spaced retrieval training over 4 weeks, with seven times a week and 1 hour a session based. The study was conducted from June 20, 2011 to July 17, 2011. Data was analyzed with descriptive statistics, $x^2$-test and t-test using the SPSS/WIN 19.0 program. Results: After spaced retrieval training, the experimental group showed significant increases in scores for memory (t=12.40, p<.001) and cognitive function (t=7.69, p<.001) in comparison to the control group. Conclusion: Spaced retrieval training was effective in increasing cognitive function and memory of patients having mild alzheimer's disease. Therefore spaced retrieval training could be benefit the mild alzheimer's disease.

• Korean Journal of Biological Psychiatry
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• v.14 no.1
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• pp.48-54
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• 2007

Objectives : This study aimed to examine the relationship between behavioral and psychological symptoms of dementia(BPSD) and patient and caregiver QOL in Alzheimer's disease(AD). Methods : Fifty-one AD patients and their caregivers participated. Measures about patients were Neuropsychiatric Inventory(NPI), Korean version of QOL-Alzheimer's Disease(KQOL-AD), Activities of Daily Living(ADL), Clinical Dementia Rating(CDR), and Korean version-Mini Mental State Examination(K-MMSE). Caregiver QOL was assessed with KQOL-AD and General Health Questionnaire/Quality of Life-12(GHQ/QOL-12). Results : Patient QOL-AD on patient ratings was negatively correlated with appetite/eating change and NPI scores. Patient QOL-AD on caregiver ratings was negatively correlated with hallucinations, depression/dysphoria, and NPI scores. Caregiver QOL assessed by the GHQ/QOL-12 was negatively correlated with agitation/aggression, depression/dysphoria, and NPI scores and was negatively correlated with distress related to agitation/aggression, depression/dysphoria, and NPI scores. Conclusion : BPSD of AD patients was associated with low QOL of both patients and caregivers. Thus, interventions of BPSD were needed to improve both patient and caregiver QOL.

• Korean Journal of Biological Psychiatry
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• v.20 no.3
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• pp.104-110
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• 2013

Objectives : The aim of this study was to examine the prospective impact of the apolipoprotein E (APOE) ${\varepsilon}4$ on cognitive performance in the community-dwelling elderly individuals with Alzheimer's disease (AD). Methods : The total number of subjects was 30 (12 men and 18 women) who were diagnosed with AD from a Korean project of "Early Detection of Dementia". People aged 65-85 years were included in the analysis. The eight neuropsychological domains from the Korean version of Consortium to Establish a Registry of Alzheimer's Disease (CERAD-K) were conducted to test subjects. They have been followed at 24-month intervals with the same assessments at each interval. Their cognitive performance at 2 year intervals was compared by the occurrence of the APOE ${\varepsilon}4$. Results : The impact of ${\varepsilon}4$ allele was significant in the Word List Memory Test (WLMT, F = 4.345, df = 1, p = 0.021) and Word List Recall Test (WLRT, F = 5.569, df = 1, p = 0.033). Conclusions : The APOE ${\varepsilon}4$ allele was significantly correlated especially with verbal episodic memory domain in community-dwelling elders diagnosed with AD.

• The Korean Journal of Nuclear Medicine
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• v.38 no.3
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• pp.209-217
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• 2004

Evaluation of dementia in patients with early symptoms of cognitive decline is clinically challenging, but the need for early, accurate diagnosis has become more crucial, since several medication for the treatment of mild to moderate Alzheimer' disease are available. Many neurodegenerative diseases produce significant brain function alteration even when structural imaging (CT or MRI) reveal no specific abnormalities. The role of PET and SPECT brain imaging in the initial assessment and differential diagnosis of dementia is beginning to evolve vapidly and growing evidence indicates that appropriate incorporation of PET into the clinical work up can improve diagnostic and prognostic accuracy with respect to Alzheimer's disease, the most common cause of dementia in the geriatric population. in the fast few years, studios comparing neuropathologic examination with PET have established reliable and consistent accuracy for diagnostic evaluations using PET - accuracies substantially exceeding those of comparable studies of diagnostic value of SPECT or of both modalities assessed side by side, or of clinical evaluations done without nuclear imaging. This review deals the role of functional brain imaging techniques in the evaluation of dementias and the role of nuclear neuroimaging in the early detection and diagnosis of Alzheimer's disease.

• Korean Journal of Biological Psychiatry
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• v.18 no.1
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• pp.36-45
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• 2011

Objectives : Though a proportion of Alzheimer's disease(AD) patients treated with donepezil have shown positive response on cognition, but the responders' characteristics are still uncertain. This study attempts to identify whether a single oral dose of donepezil(5mg) can change cognition and the relationship between single dose responder items and long-term responder are examined. Methods : Twenty-three AD patients for single donepezil challenge study group and eleven AD patients for controls were participated in the study. Seven days after baseline study for neuropsychological test and EEG, same studies were rechecked after donepezil medication in study group. In donepezil study groups, 12 weeks after donepezil medication, neuropsychological test and EEG were rechecked. Results : After single donepezil challenge, forward digit span, Rey-Osterrieth Complex Figure Test copy, SVLT delayed recall were significantly improved, and beta spectra power in anterior, theta spectra power in posterior field were significantly decreased. According to linear regression analysis, forward digit span after single donepezil challenge was significantly positive correlated with long-term responders. Conclusions : This study suggests that single donepezil medication can significantly change cognitive functions and EEG in AD patients. Among these responsive items, forward digit span was significantly correlated with long-term responder.

• Korean Journal of Biological Psychiatry
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• v.21 no.4
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• pp.115-117
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• 2014

Variety of biomarkers that are related to the Alzheimer's disease and its diagnosis and progress have been found. However, research lacks in predicting the reaction of the treatment. In addition, there is no definite treatment reaction to the disease but rather it is varied. The purpose of this review article is to study the research of the biomarkers that are able to predict the treatment reaction. There was a research that illustrated a relationship between plasma amyloid ${\beta}$ peptide, cerebrospinal fluid tau, neuroanatomical biomarkers and acetylcholinesterase inhibitors. Polymorphisms in genes of the cholinergic markers AChE, BuChE, ChAT and PON-1 were found to be associated with better clinical response to acetylcholinesterase inhibitors. Many pharmacogenetic studies have been conducted to evaluate the impact of the lipoprotein apolipoprotein E (APOE) genotype on treatment response to acetylcholinesterase inhibitor. However, there is no significant influence of the APOE genotypes on treatment response. Further research is needed to find other predictors of treatment with acetylcholinesterase inhibitors in patients with Alzheimer's disease.

• Animal cells and systems
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• v.5 no.2
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• pp.139-143
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• 2001

Alzheimer's disease is the most common form of dementia and no cure is known so far. Extensive genetic works and in vitro experiments combined with clinical observations link amyloid $\beta$--protein (A$\beta$-) to the pathogenesis of Alzheimer's disease (AD). It was hypothesized that $A\beta$- becomes toxic when it adopts a fibrillar conformation. Recently, non-fibrillar form of $A\beta$- was observed and the potential role in the pathogenesis of AD became an interesting subject. In this study, the cytotoxicity of non-fibrillar $A\beta$- and fibrillar $A\beta$- was compared on oxidative stress, membrane damage, or nucleosome break down. Non-fibrillar $A\beta$- was not toxic in peripheral nervous system-derived cells but significantly toxic in central nervous system-derived cells while fibrillar $A\beta$- was non-selectively toxic in both cell culture. The neurotoxicity of non-fibrillar $A\beta$- was reproduced in semi-in vivo culture of mouse brain slice. In conclusion, non-fibrillar $A\beta$- could be more relevant to the selective neurodegeneration in Alzheimer's brains than fibrillar $A\beta$- and further research needs to be done for identification of the cause of AD.

• International Journal of Computer Science & Network Security
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• v.21 no.8
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• pp.79-86
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• 2021

Alzheimer's is a chronic progressive disease which exhibits varied symptoms and behavioural traits from person to person. The deterioration in cognitive abilities is more noticeable through their Activities and Instrumental Activities of Daily Living rather than biological markers. This information discussed in social media communities was collected and features were extracted by using the proposed fuzzy logic based algorithm to address the uncertainties and imprecision in the data reported. The data thus obtained is used to train machine learning models in order to predict the longevity of the patients. Models built on features extracted using the proposed algorithm performs better than models trained on full set of features. Important findings are discussed and Support Vector Regressor with RBF kernel is identified as the best performing model in predicting the longevity of Alzheimer's patients. The results would prove to be of high value for healthcare practitioners and palliative care providers to design interventions that can alleviate the trauma faced by patients and caregivers due to chronic diseases.