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ISA 2024 | Machine learning-based clustering to improve risk stratification in newly diagnosed AL amyloidosis
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.
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