Deep learning for platelet transfusion
Na Li, Douglas G. Down · Blood · 2023
In this issue of Blood, Engelke et al 1 introduced a deep learning approach, specifically long short-term memory (LSTM) models, to predict the need for a platelet transfusion within the next 24 hours based on static and timedependent patient data.Platelets have a short shelf-life, which makes logistics challenging to ensure their availability when and where needed.As a result, wastage is often high.Given that platelets are donated by volunteers and are costly to the community, there is a need to make better use of the available platelet supply.The models in the study by Engelke et al explore the potential of deep learning in predicting patient platelet transfusions.