Overview: Interpretability tools make machine learning models more transparent by displaying how each feature influences ...

Explainable AI plays a central role in validating model behavior. Using established explainability techniques, the study examines which financial variables drive fraud predictions. The results show a ...

The strong role of socioeconomic factors underscores the limits of purely spatial or technical solutions. While predictive models can identify where risk concentrates, addressing why it does so ...

By contrasting nematode infection with drought stress, the study highlights both the potential and limitations of remote sensing for separating ...

Financial crime compliance in U.S. banking and financial institutions is at an inflection point. For decades, institutions ...

From Human Judgment to Algorithmic Intelligence Traditional driving relies on human perception, reaction time, and experience ...

That’s the aim of predictive cyber resilience (PCR)—an emerging approach to security built on intelligence, automation and ...

Banks and insurers must unify fragmented decisions to manage risk, regulation and customer expectations in real time.

Cognitive computing represents an innovative frontier within computer science, merging artificial intelligence, machine ...