Prediction models for COVID-19 clinical decision making
Artuur Leeuwenberg, Ewoud Schuit
Abstract
As of Sept 2, 2020, more than 25 million cases of COVID-19 have been reported, with more than 850 000 associated deaths worldwide. Patients infected with severe acute respiratory syndrome coronavirus 2, the virus that causes COVID-19, could require treatment in the intensive care unit for up to 4 weeks. As such, this disease is a major burden on health-care systems, leading to difficult decisions about who to treat and who not to.1 Prediction models that combine patient and disease characteristics to estimate the risk of a poor outcome from COVID-19 can provide helpful assistance in clinical decision making.
Topics & Concepts
ScopusCoronavirus disease 2019 (COVID-19)MedicineOverfittingIntensive care unitMEDLINEIntensive care medicineCritical appraisalSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)DiseaseAlternative medicineInternal medicinePathologyInfectious disease (medical specialty)Artificial intelligenceComputer scienceLawPolitical scienceArtificial neural networkCOVID-19 diagnosis using AISepsis Diagnosis and TreatmentMachine Learning in Healthcare