Graph neural networks in network neuroscience
Noninvasive medical neuroimaging has yielded many discoveries about the brain
connectivity. Several substantial techniques map** morphological, structural and …
connectivity. Several substantial techniques map** morphological, structural and …
Artificial general intelligence for medical imaging analysis
Large-scale Artificial General Intelligence (AGI) models, including Large Language Models
(LLMs) such as ChatGPT/GPT-4, have achieved unprecedented success in a variety of …
(LLMs) such as ChatGPT/GPT-4, have achieved unprecedented success in a variety of …
Predicting brain structural network using functional connectivity
Uncovering the non-trivial brain structure–function relationship is fundamentally important
for revealing organizational principles of human brain. However, it is challenging to infer a …
for revealing organizational principles of human brain. However, it is challenging to infer a …
Contrastive brain network learning via hierarchical signed graph pooling model
Recently, brain networks have been widely adopted to study brain dynamics, brain
development, and brain diseases. Graph representation learning techniques on brain …
development, and brain diseases. Graph representation learning techniques on brain …
Classification of alzheimer's disease via vision transformer: Classification of alzheimer's disease via vision transformer
Deep models are powerful in capturing the complex and non-linear relationship buried in
brain imaging data. However, the huge number of parameters in deep models can easily …
brain imaging data. However, the huge number of parameters in deep models can easily …
Gyri vs. sulci: Core-periphery organization in functional brain networks
The human cerebral cortex is highly convoluted into convex gyri and concave sulci. It has
been demonstrated that gyri and sulci are significantly different in their anatomy …
been demonstrated that gyri and sulci are significantly different in their anatomy …
Cp-clip: Core-periphery feature alignment clip for zero-shot medical image analysis
Multi-modality learning, exemplified by the language and image pair pre-trained CLIP
model, has demonstrated remarkable performance in enhancing zero-shot capabilities and …
model, has demonstrated remarkable performance in enhancing zero-shot capabilities and …
Jointly analyzing Alzheimer's disease related structure-function using deep cross-model attention network
Reversing the pathology of Alzheimer's disease (AD) has so far not been possible, a more
tractable way may be having the intervention in its earlier stage, such as mild cognitive …
tractable way may be having the intervention in its earlier stage, such as mild cognitive …
The benefits and risks of artificial general intelligence (agi)
M Fahad, T Basri, MA Hamza, S Faisal, A Akbar… - … (AGI) Security: Smart …, 2024 - Springer
This paper examines the idea of Artificial General Intelligence (AGI) and how it could affect
many fields. It starts by discussing how quickly artificial general intelligence (AGI) is …
many fields. It starts by discussing how quickly artificial general intelligence (AGI) is …
Cortex2vector: anatomical embedding of cortical folding patterns
Current brain map** methods highly depend on the regularity, or commonality, of
anatomical structure, by forcing the same atlas to be matched to different brains. As a result …
anatomical structure, by forcing the same atlas to be matched to different brains. As a result …