TY  - JOUR
AU  - Benito-León, Julián
AU  - Del Castillo, Mª Dolores
AU  - Estirado, Alberto
AU  - Ghosh, Ritwik
AU  - Dubey, Souvik
AU  - Serrano, J Ignacio
PY  - 2021
DO  - 10.2196/25988
UR  - https://hdl.handle.net/10668/25463
T2  - Journal of medical Internet research
AB  - Early detection and intervention are the key factors for improving outcomes in patients with COVID-19. The objective of this observational longitudinal study was to identify nonoverlapping severity subgroups (ie, clusters) among patients with...
LA  - en
KW  - COVID-19
KW  - characterization
KW  - data set
KW  - detection
KW  - emergency
KW  - intervention
KW  - machine learning
KW  - outcome
KW  - severity
KW  - subgroup
KW  - testing
KW  - Alanine Transaminase
KW  - Aspartate Aminotransferases
KW  - C-Reactive Protein
KW  - COVID-19
KW  - Cell Count
KW  - Cluster Analysis
KW  - Datasets as Topic
KW  - Emergency Service, Hospital
KW  - Humans
KW  - L-Lactate Dehydrogenase
KW  - Longitudinal Studies
KW  - Lymphocytes
KW  - Monocytes
KW  - Neutrophils
KW  - Prognosis
KW  - Spain
KW  - Triage
KW  - Unsupervised Machine Learning
TI  - Using Unsupervised Machine Learning to Identify Age- and Sex-Independent Severity Subgroups Among Patients with COVID-19: Observational Longitudinal Study.
TY  - research article
VL  - 23
ER  -