FAYETTEVILLE, GA, UNITED STATES, March 20, 2026 /EINPresswire.com/ -- Using machine learning regression models, we ...

Researchers at the University of California, San Francisco have found that machine-learning analysis of brain waves recorded during sleep can identify women at risk of cognitive decline up to five ...

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 ...

A machine-learning analysis of brain waves recorded during sleep may help identify people at high risk of developing dementia, according to a study led by UC San Francisco and Beth Israel Deaconess ...

Balancing nitrogen use is critical for maximizing crop yield while minimizing environmental and economic costs. A new approach integrates drone-based multispectral imaging with machine learning to ...

A machine-learning study finds that "brain age" calculated from sleep EEG waves can predict dementia risk, with a 10-year age gap increasing risk by 40%.

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

New architecture integrates Copilot, Azure OpenAI, Claude, and Perplexity to transform Microsoft Power BI into an ...

The frequency of substance use, early age of initiation, and cannabis-related memory impairments are among the primary factors contributing to driving under the influence, according to a new analysis ...

Discover how AI healthcare technology and machine learning diagnosis are transforming disease detection, improving accuracy, and reshaping patient care in today's evolving medical landscape.

During AY2025-2026 the CUNY Office of Research funded 16 Research in the Classroom (RIC) grants for faculty to incorporate authentic research activities into their undergraduate courses. This ...

Researchers from Edith Cowan University (ECU) are developing new technology that could change how drunk and dangerous drivers ...