Breast cancer care generates vast amounts of complex data , from imaging and pathology to genomics, that are difficult to integrate into timely clinical decisions. In our recent review, we highlight how artificial intelligence can bring these data streams together to improve detection accuracy, molecular subtyping, prognostic stratification, and treatment response prediction, while also outlining the key gaps that must be addressed before routine clinical adoption.

Read more at:https://www.nature.com/articles/s43856-025-01342-3

Chua, B.N., Thng, D.K.H., Toh, T.B. et al. Artificial intelligence for breast cancer management. Commun Med (2026). https://doi.org/10.1038/s43856-025-01342-3