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.
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 ...
As industrial environments become more connected, organizations are collecting unprecedented volumes of operational data. However, without a consistent way to organize and define that data, it can be ...
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A machine learning model may enable liver cancer risk prediction with routine clinical information
A machine learning model that analyzes patient demographics, electronic health record data, and routine blood test results ...
IAEA launches a new research project on data-driven prediction of structural changes in polymers induced by radiation. The IAEA is inviting research organizations to join a new project that will use ...
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 ...
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 ...
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