Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (31)
  • Open Access

    ARTICLE

    Enhancing Mild Cognitive Impairment Detection through Efficient Magnetic Resonance Image Analysis

    Atif Mehmood1,2, Zhonglong Zheng1,*, Rizwan Khan1, Ahmad Al Smadi3, Farah Shahid1,2, Shahid Iqbal4, Mutasem K. Alsmadi5, Yazeed Yasin Ghadi6, Syed Aziz Shah8, Mostafa M. Ibrahim7

    CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 2081-2098, 2024, DOI:10.32604/cmc.2024.046869 - 15 August 2024

    Abstract Neuroimaging has emerged over the last few decades as a crucial tool in diagnosing Alzheimer’s disease (AD). Mild cognitive impairment (MCI) is a condition that falls between the spectrum of normal cognitive function and AD. However, previous studies have mainly used handcrafted features to classify MCI, AD, and normal control (NC) individuals. This paper focuses on using gray matter (GM) scans obtained through magnetic resonance imaging (MRI) for the diagnosis of individuals with MCI, AD, and NC. To improve classification performance, we developed two transfer learning strategies with data augmentation (i.e., shear range, rotation, zoom… More >

  • Open Access

    REVIEW

    Exploring the vital role of microglial membrane receptors in Alzheimer’s disease pathogenesis: a comprehensive review

    JUN-FENG ZHAO1,†, YI-RAN JIANG2,†, TIAN-LIN GUO1, YONG-QING JIAO1,*, XUN WANG1,*

    BIOCELL, Vol.48, No.7, pp. 1011-1022, 2024, DOI:10.32604/biocell.2024.050120 - 03 July 2024

    Abstract Neurodegenerative diseases constitute a broad category of diseases caused by the degeneration of the neurons. They are mainly manifested by the gradual loss of neuron structure and function and eventually can cause death or loss of neurons. As the global population ages rapidly, increased people are being diagnosed with neurodegenerative diseases. It has been established that the onset of Alzheimer’s disease (AD) is closely linked with increasing age and its major pathological features include amyloid-beta plaques (Aβ), Tau hyperphosphorylation, Neurofibrillary tangles (NFTs), neuronal death as well as synaptic loss. The involvement of microglia is crucial… More >

  • Open Access

    ARTICLE

    RepBoTNet-CESA: An Alzheimer’s Disease Computer Aided Diagnosis Method Using Structural Reparameterization BoTNet and Cubic Embedding Self Attention

    Xiabin Zhang1,2, Zhongyi Hu1,2,*, Lei Xiao1,2, Hui Huang1,2

    CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 2879-2905, 2024, DOI:10.32604/cmc.2024.048725 - 15 May 2024

    Abstract Various deep learning models have been proposed for the accurate assisted diagnosis of early-stage Alzheimer’s disease (AD). Most studies predominantly employ Convolutional Neural Networks (CNNs), which focus solely on local features, thus encountering difficulties in handling global features. In contrast to natural images, Structural Magnetic Resonance Imaging (sMRI) images exhibit a higher number of channel dimensions. However, during the Position Embedding stage of Multi Head Self Attention (MHSA), the coded information related to the channel dimension is disregarded. To tackle these issues, we propose the RepBoTNet-CESA network, an advanced AD-aided diagnostic model that is capable… More >

  • Open Access

    ARTICLE

    An Assisted Diagnosis of Alzheimer’s Disease Incorporating Attention Mechanisms Med-3D Transfer Modeling

    Yanmei Li1,*, Jinghong Tang1, Weiwu Ding1, Jian Luo2, Naveed Ahmad3, Rajesh Kumar4

    CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 713-733, 2024, DOI:10.32604/cmc.2023.046872 - 30 January 2024

    Abstract Alzheimer’s disease (AD) is a complex, progressive neurodegenerative disorder. The subtle and insidious onset of its pathogenesis makes early detection of a formidable challenge in both contemporary neuroscience and clinical practice. In this study, we introduce an advanced diagnostic methodology rooted in the Med-3D transfer model and enhanced with an attention mechanism. We aim to improve the precision of AD diagnosis and facilitate its early identification. Initially, we employ a spatial normalization technique to address challenges like clarity degradation and unsaturation, which are commonly observed in imaging datasets. Subsequently, an attention mechanism is incorporated to More >

  • Open Access

    CORRECTION

    Correction: Prediction of Alzheimer’s Using Random Forest with Radiomic Features

    Anuj Singh*, Raman Kumar, Arvind Kumar Tiwari

    Computer Systems Science and Engineering, Vol.48, No.1, pp. 269-269, 2024, DOI:10.32604/csse.2023.047533 - 26 January 2024

    Abstract This article has no abstract. More >

  • Open Access

    REVIEW

    Realizing the potential of exploiting human IPSCs and their derivatives in research of Down syndrome

    YAFEI WANG1,2,#, JIELEI NI1,#, YUHAN LIU2, DINGYING LIAO3, QIANWEN ZHOU1, XIAOYANG JI2, GANG NIU2, YANXIANG NI1,*

    BIOCELL, Vol.47, No.12, pp. 2567-2578, 2023, DOI:10.32604/biocell.2023.043781 - 27 December 2023

    Abstract Down syndrome (DS) is a genetic condition characterized by intellectual disability, delayed brain development, and early onset Alzheimer’s disease. The use of primary neural cells and tissues is important for understanding this disease, but there are ethical and practical issues, including availability from patients and experimental manipulability. Moreover, there are significant genetic and physiological differences between animal models and humans, which limits the translation of the findings in animal studies to humans. Advancements in induced pluripotent stem cells (iPSC) technology have revolutionized DS research by providing a valuable tool for studying the cellular and molecular… More >

  • Open Access

    REVIEW

    Exploring exosomes to provide evidence for the treatment and prediction of Alzheimer’s disease

    XIANGYU QUAN1, XUETING MA1, GUODONG LI2, XUEQI FU1, JIANGTAO LI1, LINLIN ZENG1,*

    BIOCELL, Vol.47, No.10, pp. 2163-2176, 2023, DOI:10.32604/biocell.2023.031226 - 08 November 2023

    Abstract Exosomes are extracellular vesicles with a 30–150 nm diameter originating from endosomes. In recent years, scientists have regarded exosomes as an ideal small molecule carrier for the targeted treatment of Alzheimer’s disease (AD) across the blood-brain barrier due to their nanoscale size and low immunogenicity. A large amount of evidence shows that exosomes are rich in biomarkers, and it has been found that the changes in biomarker content in blood, cerebrospinal fluid, and urine are often associated with the onset of AD patients. In this paper, some recent advances in the use of exosomes in More > Graphic Abstract

    Exploring exosomes to provide evidence for the treatment and prediction of Alzheimer’s disease

  • Open Access

    ARTICLE

    Detection of Different Stages of Alzheimer’s Disease Using CNN Classifier

    S M Hasan Mahmud1,2, Md Mamun Ali3, Mohammad Fahim Shahriar1, Fahad Ahmed Al-Zahrani4, Kawsar Ahmed5,6,*, Dip Nandi1, Francis M. Bui5

    CMC-Computers, Materials & Continua, Vol.76, No.3, pp. 3933-3948, 2023, DOI:10.32604/cmc.2023.039020 - 08 October 2023

    Abstract Alzheimer’s disease (AD) is a neurodevelopmental impairment that results in a person’s behavior, thinking, and memory loss. The most common symptoms of AD are losing memory and early aging. In addition to these, there are several serious impacts of AD. However, the impact of AD can be mitigated by early-stage detection though it cannot be cured permanently. Early-stage detection is the most challenging task for controlling and mitigating the impact of AD. The study proposes a predictive model to detect AD in the initial phase based on machine learning and a deep learning approach to… More >

  • Open Access

    ARTICLE

    An Efficient 3D CNN Framework with Attention Mechanisms for Alzheimer’s Disease Classification

    Athena George1, Bejoy Abraham2, Neetha George3, Linu Shine3, Sivakumar Ramachandran4,*

    Computer Systems Science and Engineering, Vol.47, No.2, pp. 2097-2118, 2023, DOI:10.32604/csse.2023.039262 - 28 July 2023

    Abstract Neurodegeneration is the gradual deterioration and eventual death of brain cells, leading to progressive loss of structure and function of neurons in the brain and nervous system. Neurodegenerative disorders, such as Alzheimer’s, Huntington’s, Parkinson’s, amyotrophic lateral sclerosis, multiple system atrophy, and multiple sclerosis, are characterized by progressive deterioration of brain function, resulting in symptoms such as memory impairment, movement difficulties, and cognitive decline. Early diagnosis of these conditions is crucial to slowing down cell degeneration and reducing the severity of the diseases. Magnetic resonance imaging (MRI) is widely used by neurologists for diagnosing brain abnormalities.… More >

  • Open Access

    ARTICLE

    Bushen Yizhi Formula regulates the IRE1α pathway to alleviate endoplasmic reticulum stress in an Alzheimer’s disease rat model

    XIRU XU1,#, YUAN FANG1,#, BIAO ZHANG1,*, SHICHAO TENG1, XIANG WU1, JING ZHANG1, XIAOQUN GU2, MEIXIA MA3

    BIOCELL, Vol.47, No.7, pp. 1595-1609, 2023, DOI:10.32604/biocell.2023.027697 - 21 June 2023

    Abstract Background: While the Bushen Yizhi Formula can treat Alzheimer’s disease (AD), the yet to be ascertained specific mechanism of action was explored in this work. Methods: Different concentrations of the Bushen Yizhi Formula and amyloid-beta peptide (Aβ) were used to treat rat pheochromocytoma cells (P12) and human neuroblastoma cells (SH-SY5Y). Cell morphological changes were observed to determine the in vitro cell damage. Cell Counting Kit (CCK)-8 assay and flow cytometry were employed to identify cell viability and apoptosis/cell cycle, respectively. Western blotting and immunohistochemistry were employed to measure the expressions of endoplasmic reticulum stress (ERS)-related proteins (GRP78… More >

Displaying 1-10 on page 1 of 31. Per Page