Using routine clinical data, the model gauges liver cancer risk better than existing tools, offering a potential way to identify high-risk patients missed by current screening criteria.

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 ...

Researchers at Trinity College Dublin have found that a machine learning model could help clinicians predict which people ...

The IAEA is inviting research organizations to join a new project that will use machine learning to better predict structural changes in polymers caused by ionizing radiation. Rad ...

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 ...

Several Central Texas fire departments have adopted a new wildfire risk modeling tool to help firefighters better prepare and mitigate wildfire threats.

TRAVIS COUNTY, Texas (KXAN) — Several Central Texas fire departments have adopted a new wildfire risk modeling tool to help firefighters better prepare and mitigate wildfire threats. The ‘Mitigate’ ...

AUBURN, Ala. (WTVM) - Alabama Power is preparing for the spring storm season with a new predictive technology designed to reduce power outage times and better position crews before storms hit. The ...

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Cleveland-Cliffs, Inc. is a flat-rolled steel company, which engages in provision of iron ore pellets to the North American steel industry. It focuses on the production of metallic and coke, iron ...