New Digital Twin Predicts Outcomes of Brain Cancer Treatments
Researchers at the University of Michigan (U-M) have developed a system that leverages both AI and machine learning to create a digital twin of a patient’s brain cancer in order to predict how that patient will respond to different treatments. This tool promises to take personalized cancer care a step higher. The study, whose findings appeared in the journal Cell Metabolism, focused on gliomas. The team sought to establish how to distinguish between patients that are likely to benefit when their diets exclude certain amino acids (proteins) and those who are unlikely to benefit from such dietary changes. Some gliomas starve when these nutrients aren’t available in the food that a patient consumes, but some gliomas can “scavenge” for…











