Atif Mehmood^1,*, Ahed Abugabah¹, Ahmed Ali AlZubi², Louis Sanzogni³

Computer Systems Science and Engineering, Vol.43, No.1, pp. 305-315, 2022, DOI:10.32604/csse.2022.018520

Abstract Alzheimer’s disease (AD) is a neurodegenerative disorder, causing the most common dementia in the elderly peoples. The AD patients are rapidly increasing in each year and AD is sixth leading cause of death in USA. Magnetic resonance imaging (MRI) is the leading modality used for the diagnosis of AD. Deep learning based approaches have produced impressive results in this domain. The early diagnosis of AD depends on the efficient use of classification approach. To address this issue, this study proposes a system using two convolutional neural networks (CNN) based approaches for an early diagnosis of AD automatically. In the proposed… More >

RUXIN ZHANG¹, CHENGGANG LI², RUOCHEN DU¹, YITONG YUAN¹, BICHUN ZHAO¹, YUJUAN ZHANG¹, CHUNFANG WANG^1,*

BIOCELL, Vol.46, No.3, pp. 583-592, 2022, DOI:10.32604/biocell.2022.017248

Abstract Extracellular β-amyloid (Aβ) plaques and neurofibrillary tangles (NFTs) are the pathological hallmarks of Alzheimer’s disease (AD). Studies have shown that aggregates of extracellular Aβ can induce neuroinflammation mediated neurotoxic signaling through microglial activation and release of pro-inflammatory factors. Thus, modulation of Aβ might be a potential therapeutic strategy for modifying disease progression. Recently, a large number of reports have confirmed the beneficial effects of mesenchymal stem cells (MSCs) on AD. It is believed to reduce neuroinflammation, reduce Aβ amyloid deposits and NFTs, increase acetylcholine levels, promote neurogenesis, reduce neuronal damage, and improve working memory and cognition. In this review, we… More >

Himanshu Padole^*, S. D. Joshi, Tapan K. Gandhi

Intelligent Automation & Soft Computing, Vol.31, No.3, pp. 1655-1669, 2022, DOI:10.32604/iasc.2022.021310

Abstract Many methods have been proposed in the literature for diagnosis of Alzheimer's disease (AD) in the early stages, among which the graph-based methods have been more popular, because of their capability to utilize the relational information among different brain regions. Here, we design a novel graph signal processing based integrated AD detection model using multimodal deep learning that simultaneously utilizes both the static and the dynamic brain connectivity based features extracted from resting-state fMRI (rs-fMRI) data to detect AD in the early stages. First, our earlier proposed state-space model (SSM) based graph connectivity dynamics characterization method is used to design… More >

Nora Shoaip¹, Amira Rezk¹, Shaker EL-Sappagh^2,3, Tamer Abuhmed^4,*, Sherif Barakat¹, Mohammed Elmogy⁵

CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 3531-3548, 2021, DOI:10.32604/cmc.2021.019069

Abstract Alzheimer’s disease (AD) is a very complex disease that causes brain failure, then eventually, dementia ensues. It is a global health problem. 99% of clinical trials have failed to limit the progression of this disease. The risks and barriers to detecting AD are huge as pathological events begin decades before appearing clinical symptoms. Therapies for AD are likely to be more helpful if the diagnosis is determined early before the final stage of neurological dysfunction. In this regard, the need becomes more urgent for biomarker-based detection. A key issue in understanding AD is the need to solve complex and high-dimensional… More >

NARAYANAN NAMPOOTHIRI V. P.¹, VIGNESH SUNDARARAJAN¹, PALLAVI DAN¹, G. DEVANAND VENKATASUBBU^2,*, SAHABUDEEN SHEIK MOHIDEEN^1,*

BIOCELL, Vol.45, No.5, pp. 1251-1262, 2021, DOI:10.32604/biocell.2021.015090

Abstract Alzheimer’s disease (AD) is one of the most common forms of dementia. Cognitive dysfunction and memory loss are the two main clinical symptoms of AD. Drosophila melanogaster models of AD, which are based on overexpression of human amyloid β (Aβ) or human tau (hTau) protein, have been used to study the mechanism underlying AD and to screen potential therapeutic compounds. Drugs that are currently available for AD provide only symptomatic relief. Huge unmet medical needs exists to slow, stop, or reverse the progression of AD. Thymoquinone (TQ) is an active ingredient isolated from Nigella sativa (NS) and possesses various pharmacological… More >

Shuqiao Liu, Junliang Li, Xiaojie Li^*

Journal on Internet of Things, Vol.2, No.4, pp. 135-144, 2020, DOI:10.32604/jiot.2020.09797

Abstract In the deep learning field, “Capsule” structure aims to overcome the shortcomings of traditional Convolutional Neural Networks (CNN) which are difficult to mine the relationship between sibling features. Capsule Net (CapsNet) is a new type of classification network structure with “Capsule” as network elements. It uses the “Squashing” algorithm as an activation function and Dynamic Routing as a network optimization method to achieve better classification performance. The main problem of the Brain Magnetic Resonance Imaging (Brain MRI) recognition algorithm is that the difference between Alzheimer’s disease (AD) image, the Mild Cognitive Impairment (MCI) image, and the normal image is not… More >