Tag: explainable AI

A new survey in Artificial Intelligence Review proposes a unified framework linking hybrid forecasting, explainable AI and multi-agent optimization for ...

A federated learning framework combining MRI and clinical data classifies Alzheimer's disease with reported accuracy up to 94.1 percent while ...

Researchers propose a modular multi-agent framework, SoS-ML, that generates evidence-based explanations from internal model representations rather than post-hoc justifications.

A systematic review of 78 papers examines how machine learning methods support demand forecasting and inventory decision-making.

A hybrid machine learning model combining support vector regression with metaheuristic optimization predicted effluent total nitrogen at a full-scale Chinese ...

A new review maps how artificial intelligence is transforming mosquito identification, disease forecasting, and vector control worldwide.

A new promptable diffusion-enhanced framework achieved 98.1% classification accuracy and a 93.2% Dice score for explainable brain tumor segmentation and ...

A new editorial from the inaugural Lushan Summit argues that AI should personalize K-12 learning while human teachers remain irreplaceable ...

A systematic review of 75 studies finds ECG-based AI models reporting 90 to 99 percent accuracy, but warns that external ...

A study of 138 elementary students in Jakarta shows that interaction traces from VR-integrated e-modules can predict self-regulated learning with ...