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An artificial intelligence-powered method for detecting tumor DNA in blood has shown unprecedented sensitivity in predicting cancer recurrence, according to a new study. The new technology can potentially improve cancer care by detecting cancer recurrence very early and improving the monitoring of tumor response to therapy. In the study, a team led by Dr. Dan Landau of Weill Cornell Medicine and NewYork-Presbyterian Hospital showed that they could train a machine learning model, a type of artificial intelligence platform, to detect circulating tumor DNA (ctDNA) based on DNA sequencing data from patient blood tests, with very high sensitivity and accuracy. The team, which included researchers from the New York Genome Center and Memorial Sloan Kettering Cancer Center, made successful demonstrations of the technology when tested with data from patients with lung cancer, melanoma, breast cancer, colorectal cancer and precancerous colorectal polyps. https://bit.ly/45pXCJ3