A practical review of explainable AI examines how transparency and interpretability improve trust in high-stakes applications. By introducing ...

Generative Counterfactual Explainable Artificial Intelligence (XAI) offers a novel approach to understanding how AI models interpret electrocardiograms (ECGs). Traditional explanation methods focus on ...

When AI falters, it’s easy to blame the model. People assume the algorithm got it wrong or that the technology can’t be trusted. But here’s what I've learned after years of building AI systems at ...

The mainstream adoption of machine learning in investment management has created a widening gap between predictive ...

Artificial intelligence systems are becoming increasingly powerful—but also harder to understand. A new study introduces ...

We are providing an unedited version of this manuscript to give early access to its findings. Before final publication, the manuscript will undergo further editing. Please note there may be errors ...

SALT LAKE CITY, UTAH – Researchers at the University of Utah's Department of Psychiatry and Huntsman Mental Health Institute today published a paper introducing RiskPath, an open source software ...

Artificial intelligence (AI) continues to transform industries—from finance and healthcare to marketing and logistics. Yet one persistent challenge remains: trust. Many organizations see AI models as ...

A team has developed an explainable AI model for automatic collision avoidance between ships. The Titanic sunk 113 years ago on April 14-15, after hitting an iceberg ...

In todays fast evolving financial landscape, artificial intelligence and machine learning are changin how credit decisions get made. But the traditional “black box” models cause worry 'cause nobody ...

American insurers are being urged not to drag their feet on ensuring their use of AI is “explainable,” as regulators and consumers alike begin to demand it. “It’s not like this is a future issue. The ...