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 using routine clinical data more accurately predicted 5-year heart failure risk in patients with CKD ...
Patient and Caregiver Perceptions of an Interface Design to Communicate Artificial Intelligence–Based Prognosis for Patients With Advanced Solid Tumors Clinical trial data were used and contained ...
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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 ...
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Central Texas fire departments adopt AI modeling tool to predict and mitigate wildfire spread
Central Texas fire departments adopt AI modeling tool to predict and mitigate wildfire spread Posted: February 23, 2026 | Last updated: February 23, 2026 Several Central Texas fire departments have ...
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