Bilateral heterogenous emphysema was the most comment presentation in patients referred for bronchoscopic lung volume reduction (BLVR), based on data from more than 200 individuals presented at the ...

This repository contains the official PyTorch implementation and the UMC4/12 Dataset for the paper: [UrbanGraph: Physics-Informed Spatio-Temporal Dynamic Heterogeneous Graphs for Urban Microclimate ...

Microsoft Corp. today is expanding its Fabric data platform with the addition of native graph database and geospatial mapping capabilities, saying the enhancements enhance Fabric’s capacity to power ...

CEO Sam Altman called a strange graph in its GPT-5 presentation a ‘mega chart screwup.’ CEO Sam Altman called a strange graph in its GPT-5 presentation a ‘mega chart screwup.’ is a senior reporter ...

A tweet from the official Democratic Party’s X account was ridiculed on Thursday after inadvertently showing prices skyrocketing under former President Joe Biden. The post attempted to describe rising ...

ABSTRACT: Missing data remains a persistent and pervasive challenge across a wide range of domains, significantly impacting data analysis pipelines, predictive modeling outcomes, and the reliability ...

For decades, enterprise data infrastructure focused on answering the question: “What happened in our business?” Business intelligence tools, data warehouses, and pipelines were built to surface ...

Graph neural networks (GNNs) have gained traction and have been applied to various graph-based data analysis tasks due to their high performance. However, a major concern is their robustness, ...

Novel Graph Neural Network (N-GNN) Model Achieves Superior Accuracy in Early Lung Cancer Detection, Paving the Way for Enhanced Diagnostic Capabilities. Vancouver, British Columbia--(Newsfile Corp. - ...

As one of the most crucial topics in the recommendation system field, Point-of-Interest (POI) recommendation aims to recommending potential interesting POIs to users. Recently, graph neural networks ...

Graph Neural Networks (GNNs) have emerged as powerful tools for analyzing structured data, particularly in domains where relationships and interactions between entities are key. By leveraging the ...