Researchers are using machine learning to predict risks associated with stem cell therapy for myeloma, potentially enabling more personalized treatment approaches. This involves analyzing various factors, including blood biomarkers, to identify patients at higher risk of complications after transplant. The use of artificial intelligence in this context may help improve risk stratification and support early detection of post-transplant complications.