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Deep Learning Approaches for Early Prediction of Conversion from MCI to AD using MRI and Clinical Data: A Systematic Review
Due to the absence of definitive treatment for Alzheimer's disease (AD), slowing its
development is essential. Accurately predicting the conversion of mild cognitive impairment …
development is essential. Accurately predicting the conversion of mild cognitive impairment …
Fractional gradient optimized explainable convolutional neural network for Alzheimer's disease diagnosis
Alzheimer's is one of the brain syndromes that steadily affects the brain memory. The early
stage of Alzheimer's disease (AD) is referred to as mild cognitive impairment (MCI), and the …
stage of Alzheimer's disease (AD) is referred to as mild cognitive impairment (MCI), and the …
Introducing an ensemble method for the early detection of Alzheimer's disease through the analysis of PET scan images
Alzheimer's disease is a progressive neurodegenerative disorder that primarily affects
cognitive functions such as memory, thinking, and behavior. In this disease, there is a critical …
cognitive functions such as memory, thinking, and behavior. In this disease, there is a critical …
An intrusion detection system based on convolution neural network
Y Mo, H Li, D Wang, G Liu - PeerJ Computer Science, 2024 - peerj.com
With the rapid extensive development of the Internet, users not only enjoy great convenience
but also face numerous serious security problems. The increasing frequency of data …
but also face numerous serious security problems. The increasing frequency of data …
Patch-based interpretable deep learning framework for Alzheimer's disease diagnosis using multimodal data
Alzheimer's disease (AD) is a prevalent neurodegenerative disorder and a major cause of
dementia worldwide. Accurate diagnosis of AD and its prodromal stage, mild cognitive …
dementia worldwide. Accurate diagnosis of AD and its prodromal stage, mild cognitive …
Empirical Assessment of Transfer Learning Strategies for Dementia Classification Using MRI Images
Dementia is a debilitating neurodegenerative disorder affecting millions worldwide. Early
detection is very crucial for effective management. Magnetic resonance imaging (MRI) offers …
detection is very crucial for effective management. Magnetic resonance imaging (MRI) offers …
FC-Ensemble: An Ensemble Data Enhancement Method to Increase the Performance of Analysis the Staging of Alzheimer's Disease Based on Brain MRI
Alzheimer's disease is a primary degenerative encephalopathy that primarily affects the
elderly and pre-elderly population. It is characterized by persistent anxiety-like activity in the …
elderly and pre-elderly population. It is characterized by persistent anxiety-like activity in the …
Identifying Biomarker of Alzheimer's Disease Based on an Extensible Ensemble Learning Model
R Huang - 2023 5th International Conference on Frontiers …, 2023 - ieeexplore.ieee.org
Using neural network to study the potential relationship between brain genetics and imaging
has become an effective method to understand the neurodegenerative disease. At present …
has become an effective method to understand the neurodegenerative disease. At present …
A Multiscale MixFormer Network for Computer-Aided Alzheimer's Disease Diagnosis
FZ Zhu, XY Hu, X Shi, HS Xu - 2023 3rd International …, 2023 - ieeexplore.ieee.org
Deep learning has been widely utilized in medical-assisted detection and diagnosis. In the
classification and diagnosis of Alzheimer's disease (AD), deep learning can combine low …
classification and diagnosis of Alzheimer's disease (AD), deep learning can combine low …
[PDF][PDF] 深度学**在轻度认知障碍分类诊断中的应用.
周启香， 王晓燕， 张文凯， 贺鑫 - Journal of Frontiers of Computer …, 2024 - lib.zjsru.edu.cn
阿尔兹海默症是一种不可逆的神经退行性疾病, 至今尚无彻底治愈可能, 但可通过早期干预延缓
其进展. 轻度认知障碍是阿尔兹海默症的初始阶段, **确识别该阶段对阿尔兹海默症早期诊断 …
其进展. 轻度认知障碍是阿尔兹海默症的初始阶段, **确识别该阶段对阿尔兹海默症早期诊断 …