A novel federated learning framework with hybrid feature selection achieves high diagnostic accuracy across distributed medical datasets without exposing sensitive ...
Researchers developed IGWO-MRC, an optimization-guided deep learning framework that integrates chaotic swarm feature selection with residual cross-modal fusion to improve ...
A large-scale ordinal quantification study of 16,828 Reddit users affected by the 2020 Great Ban reveals that post-moderation changes in ...
A new real-time machine learning framework reduces highway structural health monitoring data storage by 91.63% while maintaining a 0.91 recall ...
Comparative laboratory testing reveals that mechanical vibration signals combined with wrapper-based machine learning provide superior diagnostic robustness over electrical current ...
A new hybrid feature selection framework combining Particle Swarm Optimization and Grey Wolf Optimizer achieves high accuracy in detecting IoT ...
Feature selection is a standard step in machine learning workflows, yet its practical value varies dramatically across different datasets.
A retrospective computational reanalysis of Gene Expression Omnibus microarray cohorts identified a candidate 13-gene transcriptomic model that achieved an out-of-fold ...
Researchers demonstrated that visible and near-infrared hyperspectral imaging combined with artificial neural networks classifies ethanol concentrations in biodiesel-ethanol-diesel fuel blends ...
A modality-aware external attention framework integrating mRNA, methylation, and miRNA data reached 86.78% accuracy in cross-validated breast cancer subtype classification ...
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