Machine learning models predicting multidrug resistant urinary tract infections using “DsaaS”

BACKGROUND: The scope of this work is to build a Machine Learning model able to predict patients risk to contract a multidrug resistant urinary tract infection (MDR UTI) after hospitalization. To achieve this goal, we used different popular Machine Learning tools. Moreover, we integrated an easy-to-...

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Detalles Bibliográficos
Autores principales: Mancini, Alessio, Vito, Leonardo, Marcelli, Elisa, Piangerelli, Marco, De Leone, Renato, Pucciarelli, Sandra, Merelli, Emanuela
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7446147/
https://www.ncbi.nlm.nih.gov/pubmed/32838752
http://dx.doi.org/10.1186/s12859-020-03566-7

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7446147/
https://www.ncbi.nlm.nih.gov/pubmed/32838752
http://dx.doi.org/10.1186/s12859-020-03566-7

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