Prediction-powered inference integrates a small gold-standard dataset with a large auxiliary dataset informed by machine ...

A machine learning model using routine clinical data more accurately predicted 5-year heart failure risk in patients with CKD ...

Sepsis is one of the most common and lethal syndromes encountered in intensive care units (ICUs), and acute respiratory ...

A machine learning model that analyzes patient demographics, electronic health record data, and routine blood test results ...

• A new AI machine learning algorithm capable of predicting planetary orbits that may one day help accelerate physics research in other areas such as renewable energy. • Strikingly, the algorithms ...

NOTE. These are the baseline variables determined at treatment completion and included in the analysis. Abbreviations: CIN, cervical intraepithelial neoplasia; COPD, chronic obstructive pulmonary ...

Ionospheric delay remains a significant error source in GNSS positioning, particularly for single-frequency users and during periods of enhanced space weather ...

Drug discovery is like molecular Tetris. Chemists snap atoms together, adjusting the pieces until everything fits and suddenly, a molecule makes a promising new medicine. Normally, creating better ...

As agent hype fades, machine learning quietly proves it’s still essential.

During the last few years or so more people have been been jumping on the artificial intelligence bandwagon and talking about its potential influence on the planet as a whole. The world is much closer ...