New York City-based Memorial Sloan Kettering Cancer Center researchers' AI sensor, trained to identify ovarian cancer, was found to be more effective than currently used methods for early detection.
The cancer detection technology, which uses an array of sensors made of carbon nanotubes that can detect certain molecules in a blood sample, combined with a machine-learning algorithm to identify a cancer fingerprint, was used in an experiment using blood samples obtained from patients with ovarian cancer, according to a May 13 press release.
Researchers found that the nanosensors detected ovarian cancer more accurately than currently available biomarker tests.
"This technology could potentially find more subtle, complex changes in the blood, which may be the key to early detection — and early detection will save lives," said Kara Roche, MD, author of the study and surgeon at Memorial Sloan Kettering.
Researchers say the technology can be adapted to detect many types of cancers using the same set of sensors, but more work is needed to confirm that this test works in people.