[HTML][HTML] Graph Neural Networks in Brain Connectivity Studies: Methods, Challenges, and Future Directions
H Mohammadi, W Karwowski - Brain Sciences, 2024 - mdpi.com
Brain connectivity analysis plays a crucial role in unraveling the complex network dynamics
of the human brain, providing insights into cognitive functions, behaviors, and neurological …
of the human brain, providing insights into cognitive functions, behaviors, and neurological …
Classification of distinct tendinopathy subtypes for precision therapeutics
C Tang, Z Wang, Y Xie, Y Fei, J Luo, C Wang… - Nature …, 2024 - nature.com
Rotator cuff tendinopathy is the most common tendinopathy type with the worst prognosis.
Conventional treatments often elicit heterogeneous drug responses due to the diversity of …
Conventional treatments often elicit heterogeneous drug responses due to the diversity of …
Self-Supervised Learning for Graph-Structured Data in Healthcare Applications: A Comprehensive Review
The abundance of complex and interconnected healthcare data offers numerous
opportunities to improve prediction, diagnosis, and treatment. Graph-structured data, which …
opportunities to improve prediction, diagnosis, and treatment. Graph-structured data, which …
Fusion of generative adversarial networks and non-negative tensor decomposition for depression fMRI data analysis
F Wang, H Ke, Y Tang - Information Processing & Management, 2025 - Elsevier
Objective: This study introduces a novel approach, F-GAN-NTD, which integrates Generative
Adversarial Networks (GANs) with Non-negative Tensor Decomposition (NTD) theory to …
Adversarial Networks (GANs) with Non-negative Tensor Decomposition (NTD) theory to …
Graph neural network with modular attention for identifying brain disorders
W Si, G Wang, L Liu, L Zhang, L Qiao - Biomedical Signal Processing and …, 2025 - Elsevier
Abstract Functional Magnetic Resonance Imaging (fMRI), by detecting the cerebral Blood
Oxygen Level-Dependent (BOLD) signals, has developed into an effective technique to aid …
Oxygen Level-Dependent (BOLD) signals, has developed into an effective technique to aid …
Motif-induced Subgraph Generative Learning for Explainable Neurological Disorder Detection
M Liu, Q Dong, C Wang, X Cheng… - … Joint Conference on …, 2024 - Springer
The wide variation in symptoms of neurological disorders among patients necessitates
uncovering individual pathologies for accurate clinical diagnosis and treatment. Current …
uncovering individual pathologies for accurate clinical diagnosis and treatment. Current …
Revolutionizing Brain Disease Diagnosis: The Convergence of AI, Genetic Screening, and Neuroimaging
L Wang, S Li, X Jin - Proceedings of the 2024 International Conference …, 2024 - dl.acm.org
The integration of artificial intelligence (AI), genetic screening, and neuroimaging heralds a
revolutionary advance in the diagnosis and understanding of brain diseases. This review …
revolutionary advance in the diagnosis and understanding of brain diseases. This review …