New Machine Learning to Identify Patients with Colorectal Cancer

A new machine learning (ML) platform can identify patients with colorectal cancer and helps predict their disease severity and survival, finds a new study. The non-invasive method adds to recent advances in technologies that analyse circulating tumour DNA (ctDNA) and could help spot colorectal cancers in at-risk patients at earlier stages. Like many other malignancies, colorectal cancers are most treatable if they are detected before they have metastasized to other tissues. Colonoscopies are the'gold standard' for diagnosis, but they are uncomfortable and invasive and can lead to complications, which leaves patients less willing to undergo screening. For the study, published in the journal Science Translational Medicine, lead researcher Huiyan Luo from University Cancer Center in China and colleagues leveraged machine learning techniques to develop a less invasive diagnostic method that can detect colorectal cancer in at-risk patients. Their technology works by screening for methylation markers, which are DNA modifications that are frequently found in tumors.