Graph-based deep learning for medical diagnosis and analysis: past, present and future
With the advances of data-driven machine learning research, a wide variety of prediction
problems have been tackled. It has become critical to explore how machine learning and …
problems have been tackled. It has become critical to explore how machine learning and …
Brain imaging-based machine learning in autism spectrum disorder: methods and applications
Autism spectrum disorder (ASD) is a neurodevelopmental condition with early childhood
onset and high heterogeneity. As the pathogenesis is still elusive, ASD diagnosis is …
onset and high heterogeneity. As the pathogenesis is still elusive, ASD diagnosis is …
Autism spectrum disorder diagnosis using graph attention network based on spatial-constrained sparse functional brain networks
C Yang, P Wang, J Tan, Q Liu, X Li - Computers in biology and medicine, 2021 - Elsevier
The accurate diagnosis of autism spectrum disorder (ASD), a common mental disease in
children, has always been an important task in clinical practice. In recent years, the use of …
children, has always been an important task in clinical practice. In recent years, the use of …
Virtual adversarial training-based deep feature aggregation network from dynamic effective connectivity for MCI identification
Dynamic functional connectivity (dFC) network inferred from resting-state fMRI reveals
macroscopic dynamic neural activity patterns for brain disease identification. However, dFC …
macroscopic dynamic neural activity patterns for brain disease identification. However, dFC …
[HTML][HTML] 医学图像深度学习技术: 从卷积到图卷积的发展
唐朝生， 胡超超， 孙君顶， 司马海峰 - 2021 - cjig.cn
摘要以卷积神经网络为代表的深度学习技术推动神经网络在医学图像研究领域不断实现新突破.
然而, 平移不变性等理论假设限制了卷积神经网络在非欧氏空间数据中的表达能力 …
然而, 平移不变性等理论假设限制了卷积神经网络在非欧氏空间数据中的表达能力 …
Identifying autism spectrum disorder based on individual-aware down-sampling and multi-modal learning
Autism Spectrum Disorder (ASD) is a set of neurodevelopmental conditions that affect
patients' social abilities. In recent years, many studies have employed deep learning to …
patients' social abilities. In recent years, many studies have employed deep learning to …
Multi-Class brain normality and abnormality diagnosis using modified Faster R-CNN
Abstract Background and Objective The detection and analysis of brain disorders through
medical imaging techniques are extremely important to get treatment on time and sustain a …
medical imaging techniques are extremely important to get treatment on time and sustain a …
脑网络分析方法及其应用.
黄嘉爽， 接标， 丁卫平， 张道强 - … & Processing/Shu Ju Cai Ji …, 2021 - search.ebscohost.com
网络结构作为一种常见的数据关系表示方法被大量运用在各类研究中. 人的大脑也可通过定义
节点和连接边的方式抽象成一个复杂的网络结构. 这个网络通常被简称为脑网络 …
节点和连接边的方式抽象成一个复杂的网络结构. 这个网络通常被简称为脑网络 …
Temporal graph representation learning for autism spectrum disorder brain networks
Modeling spatio-temporal dynamics in functional brain networks is critical for underlying the
functional mechanism of autism spectrum disorder (ASD). In our study, we propose an end …
functional mechanism of autism spectrum disorder (ASD). In our study, we propose an end …
Heterogeneous graph-based multimodal brain network learning
Graph neural networks (GNNs) provide powerful insights for brain neuroimaging technology
from the view of graphical networks. However, most existing GNN-based models assume …
from the view of graphical networks. However, most existing GNN-based models assume …