Machine learning prediction of 30-day hospital readmission for vaso-occlusive crisis in SCD patients

Caroline Vuong, MD, PhD, Amsterdam UMC, Amsterdam, The Netherlands, speaks on a single-center study conducted to develop machine learning models which can predict which patients with sickle cell disease (SCD) who were admitted to hospital for vaso-occlusive crisis will require readmission for this disease outcome within the 30-day period following discharge. Dr Vuong highlights that only a small number of patients and a year of data for each patient were required for model development, but there is a need to validate these models in other centers and countries. This interview was recorded at the 18th Annual Scientific Conference on Sickle Cell and Thalassemia (ASCAT) 2023, held in London, UK.

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