206 citations · 522 across the 32 of their papers we have counts for
10 papers · 1 filter
Transport based Graph Kernels
Kai Ma, Peng Wan, Daoqiang Zhang
Graph kernel is a powerful tool measuring the similarity between graphs. Most of the existing graph kernels focused on node labels or attributes and ignored graph hierarchical stru…
Shared Space Transfer Learning for analyzing multi-site fMRI data
Muhammad Yousefnezhad, Alessandro Selvitella, Daoqiang Zhang +2
Multi-voxel pattern analysis (MVPA) learns predictive models from task-based functional magnetic resonance imaging (fMRI) data, for distinguishing when subjects are performing diff…
ASMFS: Adaptive-Similarity-based Multi-modality Feature Selection for Classification of Alzheimer's Disease
Yuang Shi, Chen Zu, Mei Hong +6
With the increasing amounts of high-dimensional heterogeneous data to be processed, multi-modality feature selection has become an important research direction in medical image ana…
Deep Representational Similarity Learning for analyzing neural signatures in task-based fMRI dataset
Muhammad Yousefnezhad, Jeffrey Sawalha, Alessandro Selvitella +1
Similarity analysis is one of the crucial steps in most fMRI studies. Representational Similarity Analysis (RSA) can measure similarities of neural signatures generated by differen…
Ordinal Pattern Kernel for Brain Connectivity Network Classification
Kai Ma, Biao Jie, Daoqiang Zhang
Brain connectivity networks, which characterize the functional or structural interaction of brain regions, has been widely used for brain disease classification. Kernel-based metho…
An Explainable 3D Residual Self-Attention Deep Neural Network FOR Joint Atrophy Localization and Alzheimer's Disease Diagnosis using Structural MRI
Xin Zhang, Liangxiu Han, Wenyong Zhu +2
Computer-aided early diagnosis of Alzheimer's disease (AD) and its prodromal form mild cognitive impairment (MCI) based on structure Magnetic Resonance Imaging (sMRI) has provided…
A Survey on Deep Learning for Neuroimaging-based Brain Disorder Analysis
Li Zhang, Mingliang Wang, Mingxia Liu +1
Deep learning has been recently used for the analysis of neuroimages, such as structural magnetic resonance imaging (MRI), functional MRI, and positron emission tomography (PET), a…
Adaptive Feature Selection Guided Deep Forest for COVID-19 Classification with Chest CT
Liang Sun, Zhanhao Mo, Fuhua Yan +14
Chest computed tomography (CT) becomes an effective tool to assist the diagnosis of coronavirus disease-19 (COVID-19). Due to the outbreak of COVID-19 worldwide, using the computed…
Geometric Interpretation of Running Nyström-Based Kernel Machines and Error Analysis
Weida Li, Mingxia Liu, Daoqiang Zhang
Recently, Nyström method has proved its prominence empirically and theoretically in speeding up the training of kernel machines while retaining satisfactory performances and accura…
Supervised Hyperalignment for multi-subject fMRI data alignment
Muhammad Yousefnezhad, Alessandro Selvitella, Liangxiu Han +1
Hyperalignment has been widely employed in Multivariate Pattern (MVP) analysis to discover the cognitive states in the human brains based on multi-subject functional Magnetic Reson…