Machine-learning prediction models for any blood component transfusion in hospitalized dengue patients.

ABSTRACT:

Background

Blood component transfusions are a common and often necessary medical practice during the epidemics of dengue. Transfusions are required for patients when they developed severe dengue fever or thrombocytopenia of 10×10⁹/L or less. This study therefore investigated the risk factors, performance and effectiveness of eight different machine-learning algorithms to predict blood component transfusion requirements in confirmed dengue cases admitted to hospital. The objective was to study the risk factors that can help to predict blood component transfusion needs.

Methods

Eight predictive models were developed based on retrospective data from a private group of hospitals in India. A python package SHAP (SHapley Additive exPlanations) was used to explain the ou

SUBMITTER: Ansari MS 

PROVIDER: S-EPMC11670722 | biostudies-literature | 2024 Nov

REPOSITORIES: biostudies-literature