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 ...

Predictive risk scores created using administrative claims and publicly available social determinants of health data strongly ...

A wildfire forecasting system powered by artificial intelligence (AI) could help detect dangerous fire conditions earlier and ...

Researchers used a bioinformatics-plus-rat-model approach to investigate how palmatine may help treat T2DM-associated MASLD, ...

UCP Merchant Medicine, the leading provider of consulting services and clinical AI technology for Urgent Care, shared data ...

The biology behind muscle pain: calcium chaos, microscopic damage, and the overlooked mechanism that explains how statins can ...

Researchers have developed a new lipid nanoparticle design that directs mRNA to the pancreas by exploiting the organ’s own ...

Mood disorders represent a major global burden and are characterized by substantial heterogeneity in symptom profiles, treatment response, and clinical ...

Artificial intelligence enabled medical devices are changing how we think about healthcare. These tools can help doctors ...

It’s not just about having a computer in the doctor’s office anymore. We’re talking about how technology is making patient ...

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

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.