Machine Learning for Risk Stratification in DLBCL

In this MEDtalk, Mikkel Werling, PhD Student, Department of Haematology, Rigshospitalet, Copenhagen University Hospital, Denmark, discusses how machine learning can improve risk stratification and prediction of treatment failure in diffuse large B-cell lymphoma. Drawing on large-scale real-world patient data, he explains how a more comprehensive approach to patient assessment may provide more accurate and nuanced risk predictions than current clinical models.