Deep learning model predicts how individual cells influence disease outcomes

Medical Xpress March 20, 2026
Institute of Science Tokyo

A computational method called scSurv, developed by researchers at Institute of Science Tokyo, links individual cells to patient outcomes using widely available bulk RNA sequencing data. The approach uses single-cell reference datasets together with patient survival data to infer the contributions of individual cells within complex tissues. The model identified cell populations associated with survival across several cancers, offering a way to uncover disease-driving cells and support the development of more targeted treatment strategies.

What if scientists could identify the exact cells responsible for driving a disease? In a tumor, for instance, there are thousands of individual cells, each playing a unique role in driving disease progression or resisting therapy. Identifying which cells promote disease and which help counter it…