Validation of an Automated System for the Extraction of a Wide Dataset for Clinical Studies Aimed at Improving the Early Diagnosis of Candidemia

There is increasing interest in assessing whether machine learning (ML) techniques could further improve the early diagnosis of candidemia among patients with a consistent clinical picture. The objective of the present study is to validate the accuracy of a system for the automated extraction from a...

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Bibliographic Details

Published in:	Diagnostics
Main Authors:	Daniele Roberto Giacobbe, Sara Mora, Alessio Signori, Chiara Russo, Giorgia Brucci, Cristina Campi, Sabrina Guastavino, Cristina Marelli, Alessandro Limongelli, Antonio Vena, Malgorzata Mikulska, Anna Marchese, Antonio Di Biagio, Mauro Giacomini, Matteo Bassetti
Format:	Article
Language:	English
Published:	MDPI AG 2023-03-01
Subjects:	<i>Candida</i> early diagnosis machine learning relational database bloodstream infections
Online Access:	https://www.mdpi.com/2075-4418/13/5/961