Predicting blood transfusion demand in intensive care patients after surgery by comparative analysis of temporally extended data selection

Predicting blood transfusion demand in intensive care patients after surgery by comparative analysis of temporally extended data selection

Abstract Background Blood transfusion (BT) is a critical aspect of medical care for surgical patients in the Intensive Care Unit (ICU). Timely and accurate identification of BT needs can enhance patient outcomes and healthcare resource management. Methods This study aims to determine whether a machi...

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Bibliographic Details
Main Authors: Seyedmostafa Sheikhalishahi, Sebastian Goss, Lea K. Seidlmayer, Sarra Zaghdoudi, Ludwig C. Hinske, Mathias Kaspar
Format: Article
Language:English
Published: BMC 2024-12-01
Series:BMC Medical Informatics and Decision Making
Subjects:
Machine learning
Blood transfusion
Intensive care unit
Surgical patients
Predictive modeling
XGBoost
Online Access:https://doi.org/10.1186/s12911-024-02800-z
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https://doi.org/10.1186/s12911-024-02800-z

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