Zobrazeno 1 - 10
of 79
pro vyhledávání: '"Lishan Qiao"'
Publikováno v:
IEEE Transactions on Neural Systems and Rehabilitation Engineering, Vol 31, Pp 3501-3512 (2023)
Resting-state functional magnetic resonance imaging (rs-fMRI) has been widely used in the detection of brain disorders such as autism spectrum disorder based on various machine/deep learning techniques. Learning-based methods typically rely on functi
Externí odkaz:
https://doaj.org/article/7ec2e90116214a1a884e18cb89805bbc
Publikováno v:
Frontiers in Human Neuroscience, Vol 17 (2023)
There are increasing epilepsy patients suffering from the pain of seizure onsets, and effective prediction of seizures could improve their quality of life. To obtain high sensitivity for epileptic seizure prediction, current studies generally need co
Externí odkaz:
https://doaj.org/article/8a63e400330d4e4993ea2d1ebf375c70
Publikováno v:
PeerJ, Vol 11, p e14835 (2023)
Brain functional network (BFN) analysis has become a popular technique for identifying neurological/mental diseases. Due to the fact that BFN is a graph, a graph convolutional network (GCN) can be naturally used in the classification of BFN. Differen
Externí odkaz:
https://doaj.org/article/b3082cb4714445ba9537f65c5fa064c7
Publikováno v:
Frontiers in Neuroscience, Vol 16 (2022)
As one of the most common neurological disorders, epilepsy causes great physical and psychological damage to the patients. The long-term recurrent and unprovoked seizures make the prediction necessary. In this paper, a novel approach for epileptic se
Externí odkaz:
https://doaj.org/article/52ebbc2c716843fd83334dbe896f25b8
Publikováno v:
Biology, Vol 12, Iss 7, p 971 (2023)
Functional connectivity network (FCN) has become a popular tool to identify potential biomarkers for brain dysfunction, such as autism spectrum disorder (ASD). Due to its importance, researchers have proposed many methods to estimate FCNs from restin
Externí odkaz:
https://doaj.org/article/75d29ef172a14677b8af2d03f6d28ee1
Publikováno v:
Frontiers in Neuroscience, Vol 16 (2022)
Brain functional network (BFN) has become an increasingly important tool to understand the inherent organization of the brain and explore informative biomarkers of neurological disorders. Pearson’s correlation (PC) is the most widely accepted metho
Externí odkaz:
https://doaj.org/article/561d5a3056c84234a825f7aaadd1f0c0
Publikováno v:
Frontiers in Neuroinformatics, Vol 16 (2022)
Major depressive disorder (MDD) is one of the most common mental health disorders that can affect sleep, mood, appetite, and behavior of people. Multimodal neuroimaging data, such as functional and structural magnetic resonance imaging (MRI) scans, h
Externí odkaz:
https://doaj.org/article/47851578eaca44f0ac5abadde531b10e
Publikováno v:
Radiation Oncology, Vol 15, Iss 1, Pp 1-15 (2020)
Abstract Objective To perform quantitative analysis on the efficacy of using relative cerebral blood flow (rCBF) in arterial spin labeling (ASL), relative cerebral blood volume (rCBV) in dynamic magnetic sensitivity contrast-enhanced magnetic resonan
Externí odkaz:
https://doaj.org/article/c7996accae6d467e8b19a29ce92fb631
Publikováno v:
Frontiers in Neuroscience, Vol 16 (2022)
Individual identification based on brain functional network (BFN) has attracted a lot of research interest in recent years, since it provides a novel biometric for identity authentication, as well as a feasible way of exploring the brain at an indivi
Externí odkaz:
https://doaj.org/article/ead21f4f3e674e3cbafd4d9a768a1832
Publikováno v:
Frontiers in Neuroinformatics, Vol 15 (2022)
Resting-state functional MRI (rs-fMRI) has been widely used for the early diagnosis of autism spectrum disorder (ASD). With rs-fMRI, the functional connectivity networks (FCNs) are usually constructed for representing each subject, with each element
Externí odkaz:
https://doaj.org/article/332950f86eca42b483f93f5c2f2eacd4