This study highlights the potential for using deep learning methods on longitudinal health data from both primary and ...

For centuries, humans looked to seers and astrologers to determine fate. Today, we look to algorithms, and the loss of agency ...

Machine learning may help predict Fragile X-associated tremor syndrome earlier, enabling planning, monitoring, and timely ...

Researchers have shown how random forest algorithms can be applied to complex ecological models to uncover the mechanisms driving system behavior. By analyzing a stage‑structured consumer‑resource ...

Final random-forest-based models outperformed all publicly available risk scores on internal and external test sets.

Afforestation—establishing forests on previously non-forested land, or where forests have not existed for a long time—is one ...

A model integrating deep learning with clinical and epidemiologic data may significantly improve lung cancer risk prediction based on LDCT screening.

At HRS 2026, Dr. Song Zuo presented evidence that AI can detect atrial fibrillation with over 90% sensitivity, ...

An artificial intelligence (AI) model developed by researchers at The University of Texas MD Anderson Cancer Center ...

Artificial intelligence and machine learning are reshaping diabetes prevention, diagnosis, and management across the care continuum. Continuous glucose ...