Tech Xplore

New graph attention network models higher-order relationships in complex graph data

As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models ...
BMJ Open

Generating actionable insights to support point-of-care suicide risk decision-making in a safety-net healthcare system: a machine learning approach to predicting dynamic risk ...

Background Suicide rates have increased over the last couple of decades globally, particularly in the United States and among populations with lower economic status who present at safety-net ...
Reuters

Thyssenkrupp warns of deep net loss in 2026 on steel restructuring costs

Up to 800 mln euro loss seen by 2026 amid restructuring costs Proposes unchanged dividend of 15 euro cents per share Shares fall 13% in morning trading Shares fell as much as 13%, with market ...
IEEE

MRLF: Multimodal Representation Learning for Tabular Data Classification

Abstract: Representation learning fundamentally determines the classification performance of models on tabular data. However, existing tabular data classification models typically focus on ...
Reuters

As data flow revives, Fed still faces a deep policy divide

WASHINGTON, Nov 18 (Reuters) - A divided U.S. Federal Reserve begins receiving updated economic reports from the now-reopened federal government this week as policymakers hope for clarity in their ...
Scientific Research Publishing

Research on the Nonlinear Impact of Investor Sentiment on Stock Returns Based on Deep Learning and Text Mining ()

This paper focuses on the nonlinear correlation between investor sentiment and stock returns and conducts in-depth research with the aid of deep learning and text mining techniques. First of all, sort ...
C&EN

Deep Learning-Based Shape Classification for Hyperspectral-Imaged Microplastics

Article subjects are automatically applied from the ACS Subject Taxonomy and describe the scientific concepts and themes of the article. Figure 1 illustrates the overall workflow of the hyperspectral ...
Frontiers

VAE deep learning model with domain adaptation, transfer learning and harmonization for diagnostic classification from multi-site neuroimaging data

In large public multi-site fMRI datasets, the sample characteristics, data acquisition methods, and MRI scanner models vary across sites and datasets. This non-neural variability obscures neural ...
C&EN

Leveraging Deep Learning to Address Diagnostic Challenges with Insufficient Image Data

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. In recent AI-driven disease diagnosis, the success of models has depended mainly on ...