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

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

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 ...

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

Long-term sickness absence (LTSA) is a significant issue, causing productivity decline, financial difficulties, and increased mental health issues, with mental disorders being the most common cause.

• 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 ...

A machine learning model that analyzes patient demographics, electronic health record data, and routine blood test results predicted a patient's risk of hepatocellular carcinoma (HCC), the most common ...

This proposal outlines a machine learning-based approach aimed at improving productivity in haulage operations within ...

When it comes to ensuring the safety of medical and pharmaceutical products, chemical characterization plays a key role, particularly through the analysis of extractables and leachables (E&L). A ...