13 Jan A blood test for cancer shows promise thanks to machine learning
Muhammed Murtaza, professor of surgery at the UW School of Medicine and Public Health UNIVERSITY OF WISCONSIN–MADISON
A team of researchers at the University of Wisconsin–Madison has successfully combined genomics with machine learning in the quest to develop accessible tests that allow earlier detection of cancer.
For many types of cancer, early detection can lead to better outcomes for patients. While scientists are developing new blood tests that analyze DNA to aid in earlier detection, these new technologies have limitations, including cost and sensitivity.
In a study published this week in Science Translational Medicine and led by Muhammed Murtaza, professor of surgery at the UW School of Medicine and Public Health, researchers used a machine-learning model to examine blood plasma for DNA fragments from cancer cells. The technique, which uses readily available lab materials, detected cancers at an early stage among most of the samples they studied.
“We’re incredibly excited to discover that early detection and monitoring of multiple cancer types are potentially feasible using such a cost-effective approach,” says Murtaza.