8 citations · 19 across the 12 of their papers we have counts for
7 papers · 1 filter
Causal inference of brain connectivity from fMRI with -Learning Incorporated Linear non-Gaussian Acyclic Model (-LiNGAM)
Aiying Zhang, Gemeng Zhang, Biao Cai +6
Functional connectivity (FC) has become a primary means of understanding brain functions by identifying brain network interactions and, ultimately, how those interactions produce c…
A generalized kernel machine approach to identify higher-order composite effects in multi-view datasets
Md Ashad Alam, Chuan Qiu, Hui Shen +2
In recent years, a comprehensive study of multi-view datasets (e.g., multi-omics and imaging scans) has been a focus and forefront in biomedical research. State-of-the-art biomedic…
Kernel Method for Detecting Higher Order Interactions in multi-view Data: An Application to Imaging, Genetics, and Epigenetics
Md. Ashad Alam, Hui-Yi Lin, Vince Calhoun +1
In this study, we tested the interaction effect of multimodal datasets using a novel method called the kernel method for detecting higher order interactions among biologically rele…
Influence Function and Robust Variant of Kernel Canonical Correlation Analysis
Md. Ashad Alam, Kenji Fukumizu, Yu-Ping Wang
Many unsupervised kernel methods rely on the estimation of the kernel covariance operator (kernel CO) or kernel cross-covariance operator (kernel CCO). Both kernel CO and kernel CC…
Gene-Gene association for Imaging Genetics Data using Robust Kernel Canonical Correlation Analysis
Md ashad Alam, Osamu Komori, Yu-Ping Wang
In genome-wide interaction studies, to detect gene-gene interactions, most methods are divided into two folds: single nucleotide polymorphisms (SNP) based and gene-based methods. B…
Identifying Outliers using Influence Function of Multiple Kernel Canonical Correlation Analysis
Md Ashad Alam, Yu-Ping Wang
Imaging genetic research has essentially focused on discovering unique and co-association effects, but typically ignoring to identify outliers or atypical objects in genetic as wel…