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 ...

A machine learning model that analyzes patient demographics, electronic health record data, and routine blood test results ...

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 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 ...

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 ...

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) ...

Test Now Incorporates Enhanced Machine Learning Risk Prediction Algorithm Plans Underway to Commercialise Testing Service Through Trinity Biotech’s New York Reference Laboratory DUBLIN and NEW YORK, ...

Researchers are testing whether natural language processing can detect hidden psychological distress in childhood cancer survivors by analyzing their own words during clinical interviews. The approach ...