A machine learning strategy to mitigate the inappropriateness of procalcitonin request in clinical practice

A machine learning strategy to mitigate the inappropriateness of procalcitonin request in clinical practice

Aim: The aim of this study was to develop machine learning (ML) models to mitigate the inappropriate request of Procalcitonin (PCT) in clinical wards. Material and methods: We built six different ML models based on both demographical data, i.e., sex and age, and laboratory parameters, i.e., cell blo...

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Bibliographic Details
Main Authors: Luisa Agnello, Matteo Vidali, Anna Maria Ciaccio, Bruna Lo Sasso, Alessandro Iacona, Giuseppe Biundo, Concetta Scazzone, Caterina Maria Gambino, Marcello Ciaccio
Format: Article
Language:English
Published: Elsevier 2024-03-01
Series:Heliyon
Subjects:
Laboratory medicine
Sepsis
Procalcitonin
MDW
CRP
Artificial intelligence
Online Access:http://www.sciencedirect.com/science/article/pii/S2405844024025878

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http://www.sciencedirect.com/science/article/pii/S2405844024025878

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