For the first time, researchers have used machine learning—a type of artificial intelligence (AI)—to identify the most ...

UT biochemistry major Milit Patel collaborated with researchers at Memorial Sloan Kettering Cancer Center on research published in a top cancer journal.

A machine learning lung cancer risk prediction model outperformed logistic regression, supporting improved risk assessment and more efficient radiology based lung cancer screening.

Researchers from the University of Alberta and Alberta Health Services have developed a machine learning classifier algorithm that successfully predicts whether estrogen is sending signals to cancer ...

Neuroblastoma is the most common solid tumor in infants and accounts for nearly 15% of all pediatric cancer-related deaths. Despite decades of progress in surgery, chemotherapy, and stem cell ...

Thyroid cancer is the most common endocrine cancer, affecting more people each year as detection rates continue to rise.

The procedure is based around dynamic optical contrast microscopy (DOCI), a technique in development at UCLA since 2016. It ...

Using machine learning and a large volume of data on genes and existing drugs, researchers identified a combination of ...

AI and machine learning are revolutionizing drug discovery, development, and lifecycle management, addressing industry ...