A new study shows that deep learning can accurately predict the impact of environmental regulations before they are implemented, outperforming traditional expert models. Applied to the Clean Water Act ...

An analysis spanning fifty years reveals that the cost of gasoline is one of the strongest predictors of presidential approval ratings, acting in an uneven pattern where initial price spikes cause the ...

Long-term lithium therapy remains the most effective maintenance treatment for bipolar disorder, yet it poses a significant risk of progressive renal impairment in a subset of patients. Early ...

The release of the complete 2026 March Madness bracket, backed by 10,000 simulations, marks a significant milestone in the fusion of sports and data science. As the tournament unf ...

The iconic 70-year-old spy plane is receiving updates to its AN/ALQ-221 Advanced Defensive System. Despite ever changing ...

Market Size: USD 5.04 billion -- 2032 Projected Market Size: USD 10.56 billion -- CAGR (2025--2032): 11.5%. 3D Machine Visio ...

Rachael Hinkle’s work with machine learning intersects political science, legal training and computational methods.

Towards the normativity of AI-driven BCI technologies in product liability in healthcare,” published in AI & Society. In their research, the researchers analyze how emerging AI-driven ...

Abstract: Cloud detection is a crucial preliminary step for assimilating meteorological satellite observation and retrieving other atmospheric parameters. This article presents an explainable machine ...

Unsupervised learning is a branch of machine learning that focuses on analyzing unlabeled data to uncover hidden patterns, structures, and relationships. Unlike supervised learning, which requires pre ...

Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions or values from labeled historical data, enabling precise signals such as ...

Stroke is one of the leading causes of death and disability worldwide, making early screening and risk prediction crucial. Traditional methods have limitations in handling nonlinear relationships ...