Predicting Hemodynamic Failure Development in PICU Using Machine Learning Techniques

The present work aims to identify the predictors of hemodynamic failure (HF) developed during pediatric intensive care unit (PICU) stay testing a set of machine learning techniques (MLTs), comparing their ability to predict the outcome of interest. The study involved patients admitted to PICUs betwe...

Descripción completa

Detalles Bibliográficos
Autores principales: Comoretto, Rosanna I., Azzolina, Danila, Amigoni, Angela, Stoppa, Giorgia, Todino, Federica, Wolfler, Andrea, Gregori, Dario
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8303657/
https://www.ncbi.nlm.nih.gov/pubmed/34359385
http://dx.doi.org/10.3390/diagnostics11071299

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8303657/
https://www.ncbi.nlm.nih.gov/pubmed/34359385
http://dx.doi.org/10.3390/diagnostics11071299

Ejemplares similares