TY  - GEN 
AU  - Martín Loeches, Ignacio
AU  - Borges-Sa, Marcio
AU  - Gómez-Bertomeu, Frederic
AU  - Estella García, Ángel
AU  - González Garzón, Carlos
AU  - Solé Violán, Jordi
AU  - Bodí, María
A4  - Medicina
PY  - 2024
SN  - 2079-6382
UR  - http://hdl.handle.net/10498/35914
AB  - Background: Bacterial/fungal coinfections (COIs) are associated with antibiotic overuse, poor outcomes such as prolonged ICU stay, and increased mortality. Our aim was to develop machine learning-based predictive models to identify respiratory...
LA  - eng
PB  - Multidisciplinary Digital Publishing Institute (MDPI)
KW  - bacterial coinfection
KW  - COVID-19
KW  - fungal coinfection
KW  - influenza A (H1N1)
KW  - machine learning
TI  - A Machine Learning Approach to Determine Risk Factors for Respiratory Bacterial/Fungal Coinfection in Critically Ill Patients with Influenza and SARS-CoV-2 Infection: A Spanish Perspective
DO  - 10.3390/antibiotics13100968
ER  -