Shankara Anand, MD, MS, Boston University School of Medicine, Boston, MA, discusses research exploring the use of machine learning-based clustering to identify novel subgroups of patients with newly diagnosed light chain (AL) amyloidosis as an approach to improve risk stratification in this disease setting. While other risk stratification tools are currently used in clinical practice, there are some limitations with these. Dr Anand summarizes how the use of machine learning techniques allowed for the identification of three novel subgroups of patients with distinct renal and cardiac characteristics. This approach could be used to improve prognostication for newly diagnosed patients. This interview took place at the XIX International Symposium on Amyloidosis (ISA) in Rochester, MN. These works are owned by Magdalen Medical Publishing (MMP) and are protected by copyright laws and treaties around the world. All rights are reserved.