Researchers sought to determine an effective approach to predict postembolization fever in patients undergoing TACE.
Traditional machine learning models for automatic information classification require retraining data for each task. Researchers have demonstrated that art data can be automatically classified with ...
Beijing, Feb. 06, 2026 (GLOBE NEWSWIRE) -- WiMi Releases Hybrid Quantum-Classical Neural Network (H-QNN) Technology for Efficient MNIST Binary Image Classification ...
Objective This study reviewed the current state of machine learning (ML) research for the prediction of sports-related injuries. It aimed to chart the various approaches used and assess their efficacy ...
The Southern Maryland Chronicle on MSN
How are QA teams using machine learning to predict test failures in real time?
QA teams now use machine learning to analyze past test data and code changes to predict which tests will fail before they run. The technology examines patterns from previous test runs, code commits, ...
Integrating deep learning in optical microscopy enhances image analysis, overcoming traditional limitations and improving classification and segmentation tasks.
As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models designed to process graph-structured data. Currently, GNNs are effective ...
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