A new liquid biopsy approach developed by Johns Hopkins Kimmel Cancer Center investigators could revolutionize brain cancer detection by identifying circulating DNA fragments from tumors and ...

The artificial intelligence method was used to optimize an early cancer detection test to ensure high sensitivity and specificity.

Using these complex patterns from individuals with and without cancer, the researchers taught a machine learning model to identify molecular signatures associated with the four types of cancer.

A unique combination of explainable AI and repurposing animal camouflage detection algorithms can identify human brain cancer.

A novel tool for rapidly identifying the genetic "fingerprints" of cancer cells may enable future surgeons to more accurately remove brain tumors while a patient is in the operating room, new ...

Researchers have developed an AI powered model that -- in 10 seconds -- can determine during surgery if any part of a cancerous brain tumor that could be removed remains.The technology, called ...