Predicting the Need for Blood Transfusions in Cardiac Surgery: A Comparison between Machine Learning Algorithms and Established Risk Scores in the Brazilian Population

Introduction: Blood transfusion is a common practice in cardiac surgery, despite its well-known negative effects. To mitigate blood transfusion-associated risks, identifying patients who are at higher risk of needing this procedure is crucial. Widely used risk scores to predict the need for blood tr...

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Bibliografiske detaljer
Udgivet i:Revista Brasileira de Cirurgia Cardiovascular/Brazilian Journal of Cardiovascular Surgery
Main Authors: Cristiano Berardo Carneiro da Cunha, Tiago Andrade Lima, Diogo Luiz de Magalhães Ferraz, Igor Tiago Correia Silva, Matheus Kennedy Dionisio Santiago, Gabrielle Ribeiro Sena, Verônica Soares Monteiro, Lívia Barbosa Andrade
Format: Artigo
Sprog:Inglês
Udgivet: Sociedade Brasileira de Cirurgia Cardiovascular 2024
Fag:
Medicina
Cardiac Surgery
Risk Prediction
Machine Learning
Blood Transfusion
Online adgang:https://www.redalyc.org/articulo.oa?id=398977617007
https://www.redalyc.org/journal/3989/398977617007/
https://www.redalyc.org/journal/3989/398977617007/html/
https://www.redalyc.org/journal/3989/398977617007/398977617007.epub
https://www.redalyc.org/journal/3989/398977617007/movil
https://doi.org/10.21470/1678-9741-2023-0212
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