Tag: explainable AI

A new federated learning framework for chest X-ray analysis reports modest accuracy gains over existing methods while aligning explanations across ...

A new adaptive learning framework combines temporal decay weighting, sliding-window retraining and closed-loop SHAP explanations to keep intrusion detection accurate ...

Machine learning surrogates reproduce classical variance-based sensitivity results for hydrologic models at a fraction of the computational cost.

Researchers at JAIST built a graph neural network and explanation framework that locates smart contract vulnerabilities at the individual function ...

Researchers in China built an automated machine learning tool, optimized by a fox-inspired algorithm, that estimates 28-day mortality in emergency ...

Carnegie Mellon researchers developed an explainable AI framework, published in PNAS, that scores paintings for statistical patterns associated with Rembrandt, ...

A controlled study of 1,196 coffee leaf images found that an explainable Vision Transformer classified nutrient deficiencies with up to ...

A dual-channel machine-learning framework combined sentiment, academic performance and engagement data to predict educational AI adoption, learning gains and personalized ...

A hybrid DeiT system reached 99.13% accuracy on a 38-class plant disease benchmark while combining local and global AI explanations ...

A study of 303 Arabic hotel reviews found that a supervised CatBoost meta-model matched human-selected words better than standard XAI ...