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

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

Abstract 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...

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Bibliographic Details
Main Authors: Alessio Mancini, Leonardo Vito, Elisa Marcelli, Marco Piangerelli, Renato De Leone, Sandra Pucciarelli, Emanuela Merelli
Format: Article
Language:English
Published: BMC 2020-08-01
Series:BMC Bioinformatics
Subjects:
Machine learning
Classification
Regression
Data science pipeline
Antibiotic stewardship
Multi drug resistance
Online Access:http://link.springer.com/article/10.1186/s12859-020-03566-7

Internet

http://link.springer.com/article/10.1186/s12859-020-03566-7

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