Machine-learning-derived predictive score for early estimation of COVID-19 mortality risk in hospitalized patients

The clinical course of COVID-19 is highly variable. It is therefore essential to predict as early and accurately as possible the severity level of the disease in a COVID-19 patient who is admitted to the hospital. This means identifying the contributing factors of mortality and developing an easy-to...

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Veröffentlicht in:	PloS one 2022-09, Vol.17 (9), p.e0274171
Hauptverfasser:	González-Cebrián, Alba, Borràs-Ferrís, Joan, Ordovás-Baines, Juan Pablo, Hermenegildo-Caudevilla, Marta, Climente-Marti, Mónica, Tarazona, Sonia, Vitale, Raffaele, Palací-López, Daniel, Sierra-Sánchez, Jesús Francisco, Saez de la Fuente, Javier, Ferrer, Alberto
Format:	Artikel
Sprache:	eng
Schlagworte:	Adult Algorithms Analysis Biology and Life Sciences Calibration Care and treatment Chemical Sciences Classification Coronaviruses COVID-19 COVID-19 - diagnosis Creatinine Datasets Discriminant analysis Drug stores Health risks Hospital Mortality Hospital patients Hospitalization Humans L-Lactate dehydrogenase Lactate dehydrogenase Lactate Dehydrogenases Lactic acid Learning algorithms Machine Learning Medical prognosis Medical records Medical research Medicine and Health Sciences Mortality or physical chemistry Oxygen Oxygen content Pandemics Patient outcomes Patients Performance evaluation Performance measurement Physical Sciences Prediction models Research and Analysis Methods Retrospective Studies Risk Assessment Severe acute respiratory syndrome coronavirus 2 Theoretical and Variables
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