Rex Liu
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View article: Building Foundation Models to Characterize Cellular Interactions via Geometric Self-Supervised Learning on Spatial Genomics
Building Foundation Models to Characterize Cellular Interactions via Geometric Self-Supervised Learning on Spatial Genomics Open
Cellular interactions form the fundamental/core circuits that drive development, physiology, and disease within tissues. Advances in spatial genomics (SG) and artificial intelligence (AI) offer unprecedented opportunities to computationall…
View article: Metabolic dysfunctions predict the development of Alzheimer's disease: Statistical and machine learning analysis of EMR data
Metabolic dysfunctions predict the development of Alzheimer's disease: Statistical and machine learning analysis of EMR data Open
INTRODUCTION The incidence of Alzheimer's disease (AD) and obesity rise concomitantly. This study examined whether factors affecting metabolism, race/ethnicity, and sex are associated with AD development. METHODS The analyses included pati…
View article: MU-MAE: Multimodal Masked Autoencoders-Based One-Shot Learning
MU-MAE: Multimodal Masked Autoencoders-Based One-Shot Learning Open
With the exponential growth of multimedia data, leveraging multimodal sensors presents a promising approach for improving accuracy in human activity recognition. Nevertheless, accurately identifying these activities using both video data a…
View article: Gait Characterization in Duchenne Muscular Dystrophy (DMD) Using a Single-Sensor Accelerometer: Classical Machine Learning and Deep Learning Approaches
Gait Characterization in Duchenne Muscular Dystrophy (DMD) Using a Single-Sensor Accelerometer: Classical Machine Learning and Deep Learning Approaches Open
Differences in gait patterns of children with Duchenne muscular dystrophy (DMD) and typically developing (TD) peers are visible to the eye, but quantifications of those differences outside of the gait laboratory have been elusive. In this …
View article: Uncovering the Gut–Liver Axis Biomarkers for Predicting Metabolic Burden in Mice
Uncovering the Gut–Liver Axis Biomarkers for Predicting Metabolic Burden in Mice Open
Western diet (WD) intake, aging, and inactivation of farnesoid X receptor (FXR) are risk factors for metabolic and chronic inflammation-related health issues ranging from metabolic dysfunction-associated steatotic liver disease (MASLD) to …
View article: Machine Learning to Identify Molecular Markers for Metabolic Disease Development Using Mouse Models
Machine Learning to Identify Molecular Markers for Metabolic Disease Development Using Mouse Models Open
Background Aging, Western diet (WD) intake, and bile acid (BA) receptor farnesoid X receptor (FXR) inactivation are risk factors for metabolic disease development including nonalcoholic fatty liver disease (NAFLD) and chronic inflammation-…
View article: MASTAF: A Model-Agnostic Spatio-Temporal Attention Fusion Network for Few-shot Video Classification
MASTAF: A Model-Agnostic Spatio-Temporal Attention Fusion Network for Few-shot Video Classification Open
We propose MASTAF, a Model-Agnostic SpatioTemporal Attention Fusion network for few-shot video classification. MASTAF takes input from a general video spatial and temporal representation,e.g., using 2D CNN, 3D CNN, and Video Transformer. T…
View article: Early Mobility Recognition for Intensive Care Unit Patients Using Accelerometers
Early Mobility Recognition for Intensive Care Unit Patients Using Accelerometers Open
With the development of the Internet of Things(IoT) and Artificial Intelligence(AI) technologies, human activity recognition has enabled various applications, such as smart homes and assisted living. In this paper, we target a new healthca…
View article: Gait Characterization in Duchenne Muscular Dystrophy (DMD) Using a Single-Sensor Accelerometer: Classical Machine Learning and Deep Learning Approaches
Gait Characterization in Duchenne Muscular Dystrophy (DMD) Using a Single-Sensor Accelerometer: Classical Machine Learning and Deep Learning Approaches Open
Differences in gait patterns of children with Duchenne muscular dystrophy (DMD) and typically-developing (TD) peers are visible to the eye, but quantifications of those differences outside of the gait laboratory have been elusive. In this …