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Is attention all you need in medical image analysis? A review
Medical imaging is a key component in clinical diagnosis, treatment planning and clinical
trial design, accounting for almost 90% of all healthcare data. CNNs achieved performance …
trial design, accounting for almost 90% of all healthcare data. CNNs achieved performance …
A review of the application of three-dimensional convolutional neural networks for the diagnosis of Alzheimer's disease using neuroimaging
X Xu, L Lin, S Sun, S Wu - Reviews in the Neurosciences, 2023 - degruyter.com
Alzheimer's disease (AD) is a degenerative disorder that leads to progressive, irreversible
cognitive decline. To obtain an accurate and timely diagnosis and detect AD at an early …
cognitive decline. To obtain an accurate and timely diagnosis and detect AD at an early …
Applications of deep learning in Alzheimer's disease: A systematic literature review of current trends, methodologies, challenges, innovations, and future directions
S Toumaj, A Heidari, R Shahhosseini… - Artificial Intelligence …, 2024 - Springer
Alzheimer's Disease (AD) constitutes a significant global health issue. In the next 40 years, it
is expected to affect 106 million people. Although more and more people are getting AD …
is expected to affect 106 million people. Although more and more people are getting AD …
Investigating deep learning for early detection and decision-making in alzheimer's disease: a comprehensive review
Alzheimer's disease (AD) is a neurodegenerative disorder that affects millions of people
worldwide, making early detection essential for effective intervention. This review paper …
worldwide, making early detection essential for effective intervention. This review paper …
Deep multimodality-disentangled association analysis network for imaging genetics in neurodegenerative diseases
Imaging genetics is a crucial tool that is applied to explore potentially disease-related
biomarkers, particularly for neurodegenerative diseases (NDs). With the development of …
biomarkers, particularly for neurodegenerative diseases (NDs). With the development of …
Transformer-based approaches for neuroimaging: an in-depth review of their role in classification and regression tasks
X Zhu, S Sun, L Lin, Y Wu, X Ma - Reviews in the Neurosciences, 2025 - degruyter.com
In the ever-evolving landscape of deep learning (DL), the transformer model emerges as a
formidable neural network architecture, gaining significant traction in neuroimaging-based …
formidable neural network architecture, gaining significant traction in neuroimaging-based …
Wide and deep learning based approaches for classification of Alzheimer's disease using genome-wide association studies
The increasing incidence of Alzheimer's disease (AD) has been leading towards a
significant growth in socioeconomic challenges. A reliable prediction of AD might be useful …
significant growth in socioeconomic challenges. A reliable prediction of AD might be useful …
Modality-aware discriminative fusion network for integrated analysis of brain imaging genomics
Mild cognitive impairment (MCI) represents an early stage of Alzheimer's disease (AD),
characterized by subtle clinical symptoms that pose challenges for accurate diagnosis. The …
characterized by subtle clinical symptoms that pose challenges for accurate diagnosis. The …
Deep learning-based feature extraction with MRI data in neuroimaging genetics for Alzheimer's disease
The prognosis and treatment of patients suffering from Alzheimer's disease (AD) have been
among the most important and challenging problems over the last few decades. To better …
among the most important and challenging problems over the last few decades. To better …
Fusion of brain imaging genetic data for alzheimer's disease diagnosis and causal factors identification using multi-stream attention mechanisms and graph …
Correctly diagnosing Alzheimer's disease (AD) and identifying pathogenic brain regions and
genes play a vital role in understanding the AD and develo** effective prevention and …
genes play a vital role in understanding the AD and develo** effective prevention and …