This valuable study uses EEG and computational modeling to investigate hemispheric oscillatory asymmetries in unilateral spatial neglect. The work benefits from rare patient data and a careful ...

Making causal inferences about illness, compared to making causal inferences about mechanical breakdown and reading causally unconnected sentences, activates a semantic brain network implicated in the ...

For decades, artificial intelligence has excelled at spotting patterns in data. Machine learning models can predict customer behavior, forecast market trends, or identify medical risks with high ...

The reduction of health inequalities has been a priority of researchers, decision-makers and practitioners for many years.

Causely's reasoning engine models how distributed systems behave, identifying the cause of reliability risks, their impacts, and the actions required to assure performance. With Google's Gemini models ...

Abstract: Data-driven fault detection has gained substantial attention in recent times. Graph-based models, which incorporate spatial information for feature extraction, have shown promising results, ...

Abstract: A two-area Automatic Generation Control (AGC) model is utilized to evaluate the performance of PID, ANN, and ANFIS controllers, with a novel approach of combining all three controllers into ...