Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Predicting the Need for Blood Transfusions in Cardiac Surgery: A Comparison between Machine Learning Algorithms and Established Risk Scores in the Brazilian Population
3
Zitationen
8
Autoren
2024
Jahr
Abstract
The findings of this study suggest that ML algorithms may offer a more accurate prediction of the need for blood transfusions than the traditional scoring systems and could enhance the accuracy of predicting blood transfusion requirements in cardiac surgery patients. Further research could focus on optimizing and refining ML algorithms to improve their accuracy and make them more suitable for clinical use.
Ähnliche Arbeiten
A Multicenter, Randomized, Controlled Clinical Trial of Transfusion Requirements in Critical Care
1999 · 5.189 Zit.
Effects of tranexamic acid on death, vascular occlusive events, and blood transfusion in trauma patients with significant haemorrhage (CRASH-2): a randomised, placebo-controlled trial
2010 · 3.214 Zit.
Transfusion of Plasma, Platelets, and Red Blood Cells in a 1:1:1 vs a 1:1:2 Ratio and Mortality in Patients With Severe Trauma
2015 · 2.401 Zit.
A Multicenter, Randomized, Controlled Clinical Trial of Transfusion Requirements in Critical Care
1999 · 2.044 Zit.
Correction of the Anemia of End-Stage Renal Disease with Recombinant Human Erythropoietin
1987 · 2.019 Zit.