189 citations · 888 across the 107 of their papers we have counts for
5 papers · 2 filters
Coherence-based Time Series Clustering for Brain Connectivity Visualization
Carolina Euan, Ying Sun, Hernando Ombao
We develop the hierarchical cluster coherence (HCC) method for brain signals, a procedure for characterizing connectivity in a network by clustering nodes or groups of channels tha…
A Robust Interrupted Time Series Model for Analyzing Complex Healthcare Intervention Data
Maricela Cruz, Miriam Bender, Hernando Ombao
Current health policy calls for greater use of evidence based care delivery services to improve patient quality and safety outcomes. Care delivery is complex, with interacting and…
Multi-Scale Factor Analysis of High-Dimensional Brain Signals
Chee-Ming Ting, Hernando Ombao, Sh-Hussain Salleh
In this paper, we develop an approach to modeling high-dimensional networks with a large number of nodes arranged in a hierarchical and modular structure. We propose a novel multi-…
Modeling high dimensional multichannel brain signals
Lechuan Hu, Norbert Fortin, Hernando Ombao
Our goal is to model and measure functional and effective (directional) connectivity in multichannel brain physiological signals (e.g., electroencephalograms, local field potential…
Estimating Time-Varying Effective Connectivity in High-Dimensional fMRI Data Using Regime-Switching Factor Models
Chee-Ming Ting, Hernando Ombao, S. Balqis Samdin +1
Recent studies on analyzing dynamic brain connectivity rely on sliding-window analysis or time-varying coefficient models which are unable to capture both smooth and abrupt changes…