TY  - JOUR
AU  - Garnica Alcázar, Antonio Óscar
AU  - Gómez, Diego
AU  - Ramos, Víctor
AU  - Hidalgo González, José Ignacio
AU  - Ruiz Giardín, José Manuel
PY  - 2021
DO  - 10.1007/s13167-021-00252-3
SN  - 1878-5077
UR  - https://hdl.handle.net/20.500.14352/4708
T2  - EPMA Journal
AB  - BackgroundThe bacteraemia prediction is relevant because sepsis is one of the most important causes of morbidity and mortality. Bacteraemia prognosis primarily depends on a rapid diagnosis. The bacteraemia prediction would shorten up to 6 days the...
LA  - eng
M2  - 365
PB  - Springer Nature
KW  - Predictive
KW  - Preventive and personalised medicine (PPPM/3PM)
KW  - Machine learning
KW  - Modelling
KW  - Bacteraemia diagnosis
KW  - Bacteraemia prediction
KW  - Blood culture’s outcome prediction
KW  - Individualised electronic patient record analysis
KW  - Personalised antibiotic treatment
KW  - Support vector machine
KW  - Random forest
KW  - K-Nearest neighbours
KW  - Healthcare economy
KW  - Health policy
KW  - COVID-19
TI  - Diagnosing hospital bacteraemia in the framework of predictive, preventive and personalised medicine using electronic health records and machine learning classifiers
TY  - journal article
VL  - 12
ER  -