Researchers have developed and validated a machine learning--based method to predict which patients with early-stage melanoma are most likely to experience a cancer recurrence.

Researchers have developed and validated a machine learning-based method to predict which patients with early-stage melanoma are most likely to experience a cancer recurrence.

BERIL-1: Biomarker results from targeted sequencing of circulating tumor DNA (ctDNA) and archival tissue in a randomized phase II study of buparlisib (BKM120) or placebo plus paclitaxel in patients ...

Most deaths from melanoma—the most lethal form of skin cancer—occur in patients who were initially diagnosed with early-stage melanoma and then later experienced a recurrence that is typically not ...

Risk stratification can be accurately modeled via a tree-based method. Future research should layer in other outcomes, such as comorbidity, ongoing treatment toxicities, or risk of delayed treatment, ...

Domestic researchers have developed a diagnostic method that can early predict the risk of recurrence in breast cancer patients using their blood. This method is especially applicable to ...