IEEE

A Data-Driven Graph Model Approach to Critical Care Patient Clinical Trajectory Prediction

Abstract: The advent of increasingly available patient health data has created opportunities for critical care medicine to embrace modern data-driven decision support. However, existing methods, such ...
GitHub

FedDGL: Federated Dynamic Graph Learning for Temporal Evolution and Data Heterogeneity

Federated graph learning advances the field of federated learning by enabling privacy-preserving collaborative training on distributed graph data. Conventional federated graph learning methods excel ...
GitHub

The Connected Data Knowledge Graph Challenge

The Connected Data platform provides a Community, Events, and Thought Leadership for those who use the Relationships, Meaning and Context in Data to achieve great things. We've been Connecting Data, ...
IEEE

sigRGCN: A Robust Residual Graph Convolutional Network for scRNA-Seq Data Clustering

Abstract: Clustering is a crucial step in single-cell RNA sequencing (scRNA-seq) data analysis, facilitating the discovery of new cell types and the grouping of similar cells. Recently, graph ...