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52 results for “Alzheimer’s”
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Research ArticleOpen accessEvery word in the titleAn AI-Powered Integrated Care Model Combining Traditional Chinese Medicine and Western Medicine for Personalized Alzheimer’s Disease ManagementShurong Li, Yiming Chen, Jin Xu et al.Alzheimer's Disease (AD) gradually reduces memory and cognition. While Western medicine focuses on pharmacological treatments, it frequently ignores holistic factors such as mood and digestion. Traditional Chinese Medicine (TCM) addresses these issues through a wellness-oriented approach. However, the combination of both systems in patient care is uncommon. Current Alzheimer's disease treatments are often siloed, relying solely on Western or alternative … …American Journal of Biochemistry and Biotechnology, Vol. 21, Issue 4 · 16 Feb 2026 · 2,063 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleUsing Deep Learning to Support Clinical Decision-Making: The Case of Alzheimer’s Disease DiagnosisNawal Mohamed Bahy Eldin, Ghada A. El Khayat, Abeer A. AmerAlzheimer’s disease is a chronic, progressive brain disorder that leads to a gradual decline in memory and cognitive functions. In this study, N-VGG16, an advanced deep learning model, is proposed. The model builds upon the VGG16 architecture, incorporating key enhancements to improve its ability to classify neurodegenerative conditions. The model processes structural neuroimaging data using a refined pipeline that applies … …Journal of Computer Science, Vol. 21, Issue 10 · 11 Dec 2025 · 3,383 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleA Vertical Stacking-Based Ensemble Deep Learning Model for Early Diagnosis of Alzheimer's Disease Using Multimodal MRI ScansParvatham Niranjan Kumar, Lakshmana Phaneendra MaguluriEarly detection of Alzheimer's Disease (AD) is crucial for timely interventions that can slow disease progression, enhance quality of life, and assist with future planning. Convolutional Neural Networks (CNNs) are an efficient method for processing image-based data. In this work, we used CNN-based deep learning models to extract structural information from structural MRI (sMRI) and brain neuron connectivity patterns from … …Journal of Computer Science, Vol. 21, Issue 6 · 14 Jun 2025 · 3,099 accessesView PDFCite
Literature ReviewOpen accessEvery word in the titleAtherosclerosis and Alzheimer’s Disease Interconnection: Inflammation, Aβ and MoreAnastasia Vladimirovna Poznyak, Victoria Khotina, Roghayyeh Vakili-Ghartavol et al.Despite being the leading cause of CVD and cardiovascular mortality globally, Atherosclerosis (ATH) remains underdiagnosed and undertreated. The reasons behind Alzheimer’s Disease (AD) also remain unclear and there is currently no cure for it. At present, at least 55 million people are believed to be suffering from the disorder and the figures are expected to grow. At the same time, … …OnLine Journal of Biological Sciences, Vol. 24, Issue 4 · 26 May 2024 · 4,761 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleAnalysis of Plasma Amyloid-Beta and Apolipoprotein E Genotypes as Markers of Alzheimer’s Disease in Healthy Korean AdultsEun Ju Oh, Jung Jae Lee, Bo Kyeung Jung, Jae Kyung KimThe presence of the ApoE4 allele interferes with human Amyloid-Beta (Aβ) clearance and reduces the neuronal damage response, which, in turn, is associated with increased Alzheimer’s Disease (AD) risk. Identifying individuals with the highest genetic risk may aid clinical AD diagnosis and prognosis. However, to the best of our knowledge, no previous study has performed blood-based analysis of ApoE polymorphisms … …American Journal of Biochemistry and Biotechnology, Vol. 20, Issue 1 · 26 Mar 2024 · 4,492 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleWhale Optimized Deep Generative Adversarial Network Based Alzheimer's Stages Detection Using 3D MRI Brain NeuroimagingR. Sampath, M. BaskarAlzheimer's Disease (AD), a common, chronic neurodegenerative condition, is characterized by the loss of neurons and synapses in the cerebral cortex and specific subcortical regions. According to claims from a recent study, AD has a 20% misdiagnosis rate. Therefore, it is essential to create a useful tool to recognize the stages of AD with a lower prediction error rate to … …Journal of Computer Science, Vol. 19, Issue 8 · 4 Aug 2023 · 5,544 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleImage-Based Alzheimer's Disease Detection Using Pretrained Convolutional Neural Network ModelsNasser AlsadhanAlzheimer's disease is an untreatable, progressive brain disorder that slowly robs people of their memory, thinking abilities, and ultimately their capacity to complete even the most basic tasks. Among older adults, it is the most frequent cause of dementia. Although there is presently no treatment for Alzheimer's disease, scientific trials are ongoing to discover drugs to combat the condition. Treatments … …Journal of Computer Science, Vol. 19, Issue 7 · 28 Jun 2023 · 5,909 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleImproved Classification Model using CNN for Detection of Alzheimer’s DiseaseRagavamsi Davuluri, Ragupathy RengaswamyAlzheimer’s Disease (AD) is commonly called a neurodegenerative disorder and it is a common form of dementia. There is no permanent cure for this brain disease hence the early diagnosis of such disease using medical imaging system is highly significant. Machine learning models play a vital role in the detection of AD. Since most of the conventional machine learning models … …Journal of Computer Science, Vol. 18, Issue 5 · 30 May 2022 · 6,252 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleDiagnosing Alzheimer’s Disease using Convolution Neural NetworksSarita, Saurabh Mukherjee, Tanupriya Choudhury et al.Alzheimer’s is a disease wherein constant degeneration of neurons and their synapses result in impaired brain functioning which leads to personality changes, memory loss, thinking and speech disorder. So, there is a requirement of an automated and early diagnosis of this disease to decrease the death rate. The proposed work is coupled with deep learning techniques to predict the Alzheimer’s … …Journal of Computer Science, Vol. 18, Issue 2 · 21 Feb 2022 · 7,344 accessesView PDFCite
Literature ReviewOpen accessEvery word in the titleEfficient Morphometric Techniques in Alzheimer’s Disease Detection: Survey and ToolsVinutha N., P. Deepa Shenoy, K.R. VenugopalThe development of advance techniques in the multiple fields such as image processing, data mining and machine learning are required for the early detection of Alzheimer’s Disease (AD) and to prevent the progression of the disease to the later stages. The longitudinal and cross sectional images of elderly subjects were obtained from the standard datasets like ADNI, OASIS, MIRIAD and … …Neuroscience International, Vol. 7, Issue 2 · 4 Oct 2017 · 8,450 accessesView PDFCite