Among patients with chronic noncancer pain, a novel machine learning model effectively predicts opioid use disorder risk.

A US robotics company has quietly assembled what amounts to a colossal digital forest, training an artificial intelligence ...

A machine learning model incorporating functional assessments predicts one-year mortality in older patients with HF and improves risk stratification beyond established scores. Functional status at ...

IMF researchers show that satellite data, especially nighttime lights combined with machine learning can reliably estimate ...

Background Early graft failure within 90 postoperative days is the leading cause of mortality after heart transplantation. Existing risk scores, based on linear regression, often struggle to capture ...

Scientists have created an AI model that forecasts moderate heat stress—a major precursor to coral bleaching—at sites along ...

Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions ...

Recentive Analytics, Inc. v. Fox Corp., No. 23-2437 (Fed. Cir. 2025) – On April 18, 2025, the Federal Circuit upheld the district court’s dismissal of the case on the ground that the patents were ...

The absence of reliable data on fundamental economic indicators (e.g. real GDP), combined with structural shifts in the economy, can severely constrain the ability to conduct accurate macroeconomic ...

A new study published in the journal of Scientific Reports proposed a potential diagnostic tool by combining deep learning ...

RFX-Fuse (Random Forests X [X=compression] — Forest Unified Learning and Similarity Engine) delivers Breiman and Cutler's complete vision for Random Forests as a Forests Unified Machine Learning and ...

Recent study reveals machine learning's potential in predicting the strength of carbonated recycled concrete, paving the way ...