New research using AI-powered stacked ensemble models has improved accuracy in predicting NBA game results by combining multiple machine learning algorithms. These models not only forecast outcomes ...

A new study by Justin Grandinetti of the University of North Carolina at Charlotte challenges one of the most dominant narratives in artificial intelligence: that modern AI systems are inherently ...

Researchers conducted a systematic review to assess the risk of bias and applicability of prediction models for fear of recurrence in patients with cancer.

Researchers have unveiled an interpretable, lightweight AI text detection framework using classical machine learning models that achieves near-perfect accuracy while lowering computational costs.

Built on a new architecture KumoRFM-2 achieves state-of-the-art results across 41 predictive tasks and four major benchmarks, ...

In my latest Signal Spot, I had my Villanova students explore machine learning techniques to see if we could accurately ...

Trained on historical consumption data spanning a decade, the model demonstrated strong predictive performance. It achieved a training error of 0.182 and a forecasting accuracy of 95.2 percent, ...

A new satellite-based analytical framework enables accurate estimation of crop sowing and emergence dates at the field scale.

A new satellite-based analytical framework enables accurate estimation of crop sowing and emergence dates at the field scale. By integrating daily ...

Methane is the second most important anthropogenic greenhouse gas after carbon dioxide, with a global warming potential roughly 28–34 times greater over a 100-year timescale. Major sources include ...