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

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

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

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

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

IPDsim: An interpretable model to assess individual clinical antagonism in combination therapies for cancers. Model performance across development and validation cohorts.

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

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 ...

Researchers at The University of Manchester have created a physics‑informed machine‑learning model that can run molecular ...