TY  - JOUR
AU  - Klen, Riku
AU  - Purohit, Disha
AU  - Gomez-Huelgas, Ricardo
AU  - Casas-Rojo, Jose Manuel
AU  - Anton-Santos, Juan Miguel
AU  - Nuñez-Cortes, Jesus Millan
AU  - Lumbreras, Carlos
AU  - Ramos-Rincon, Jose Manuel
AU  - Garcia-Barrio, Noelia
AU  - Pedrera-Jimenez, Miguel
AU  - Lalueza-Blanco, Antonio
AU  - Martin-Escalante, Maria Dolores
AU  - Rivas-Ruiz, Francisco
AU  - Onieva-Garcia, Maria Angeles
AU  - Young, Pablo
AU  - Ramirez, Juan Ignacio
AU  - Titto-Omonte, Estela Edith
AU  - Gross-Artega, Rosmery
AU  - Canales-Beltran, Magdy Teresa
AU  - Valdez, Pascual Ruben
AU  - Pugliese, Florencia
AU  - Castagna, Rosa
AU  - Huespe, Ivan A
AU  - Boietti, Bruno
AU  - Pollan, Javier A
AU  - Funke, Nico
AU  - Leiding, Benjamin
AU  - Gomez-Varela, David
PY  - 2022
DO  - 10.7554/eLife.75985
UR  - http://hdl.handle.net/10668/21673
T2  - eLife
AB  - New SARS-CoV-2 variants, breakthrough infections, waning immunity, and sub-optimal vaccination rates account for surges of hospitalizations and deaths. There is an urgent need for clinically valuable and generalizable triage tools assisting the...
LA  - en
PB  - eLife Sciences Publications
KW  - COVID-19
KW  - Computational biology
KW  - Human
KW  - Machine-learning
KW  - Medicine
KW  - Prediction
KW  - Systems biology
KW  - Triage
KW  - COVID-19
KW  - Hospitalization
KW  - Hospitals
KW  - Humans
KW  - Machine Learning
KW  - Retrospective Studies
KW  - SARS-CoV-2
TI  - Development and evaluation of a machine learning-based in-hospital COVID-19 disease outcome predictor (CODOP): A multicontinental retrospective study.
TY  - research article
VL  - 11
ER  -