Machine learning algorithms in sepsis

•Machine learning models are promising for the early diagnosis and prognosis of sepsis.•There is still high heterogeneity among studies.•The appropriate interpretation by a multidisciplinary approach, including professionals with different skills, is mandatory. Sepsis remains a significant global he...

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Bibliographic Details

Published in:	Clinica chimica acta Vol. 553; p. 117738
Main Authors:	Agnello, Luisa, Vidali, Matteo, Padoan, Andrea, Lucis, Riccardo, Mancini, Alessio, Guerranti, Roberto, Plebani, Mario, Ciaccio, Marcello, Carobene, Anna
Format:	Journal Article
Language:	English
Published:	Netherlands Elsevier B.V 15.01.2024
Subjects:	Artificial intelligence Laboratory medicine Machine learning Random forest Sepsis Tests Sepsis Random forest Laboratory medicine Artificial intelligence Tests Machine learning
ISSN:	0009-8981, 1873-3492, 1873-3492
Online Access:	Get full text
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