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 ...

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 that analyzes patient demographics, electronic health record data, and routine blood test results ...

Yale researchers have developed a machine learning model, called Immunostruct, that can help scientists create more personalized vaccines, including vaccines for cancer. They described the tool in ...

What are the benefits and challenges of using multiomics approaches to discover cancer biomarkers? Multiomics means that scientists are measuring more than one class of analyte, such as DNA, RNA, or ...

A new research paper featured on the cover of Volume 17, Issue 11 of Aging-US was published on October 30, 2025, titled "SAMP-Score: a morphology-based machine learning classification method for ...

We trained and tested ML systems that predict a deterioration in nine patient-reported symptoms within 30 days after treatments for aerodigestive cancers, using internal electronic health record (EHR) ...

The intriguing story that went viral online gained significant global attention in March 2026, demonstrating how a determined ...