Evaluation of machine learning pipeline for blood culture outcome prediction on prospectively collected data in Western Australian emergency department
Benjamin McFadden,
Timothy Inglis,
Antonio Celenza
et al.
Abstract:Bloodstream infections (BSIs) are particularly problematic in the emergency department (ED) of hospitals, where patients often present with undifferentiated illness, and the presence of BSI is hard to detect. Identifying whether a patient needs a blood culture (BC) test performed is one component of this challenge with implications for diagnostic efficiency, stewardship, and unnecessary resource expenditure. This paper explores the validation of previously developed machine learning (ML) models for BC outcome … Show more
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