Tag: explainable AI

An open-access study combined label-free brightfield microscopy, machine learning, and SHAP-based explainability to classify 17,781 red blood cells across ten ...

A new hybrid explainable machine learning framework combines satellite environmental data with health records to predict cardiovascular disease risk at ...

A systematic review of 64 studies finds that only about one in five AI prediction models built on electronic health ...

A Radial Basis Function network achieved the strongest performance among fifteen AI models used to predict CO2 emissions across 15 ...

A scoping review of 50 studies finds that Egypt's cybercrime law recognizes digital evidence but lacks mandatory tool validation, laboratory ...

Researchers have built an explainable stacking machine learning framework that jointly forecasts electrical load and predicts transformer remaining lifespan in ...

A new review argues that trustworthy agricultural autonomy depends on integrating robot learning, safe control and human-robot interaction rather than ...

A new open access survey reviews AI methods for operating power grids with high penetration of distributed energy resources and ...

Researchers propose a conceptual framework called CyTS that organizes human–AI collaboration into four layers while explicitly withholding claims of validated ...

Researchers report a Mamba-BiLSTM framework with Granger-inspired directional causal fusion that reached 81.86 percent accuracy for multimodal depression detection on ...