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Utilization of machine-learning models to accurately predict the risk for critical COVID-19

Dan Assaf, Ya’ara Gutman, Yair Neuman, Gad Segal, Sharon Amit, Shiraz Gefen-Halevi, Noya Shilo, Avi Epstein, Ronit Mor-Cohen, Asaf Biber, Galia Rahav, Itzchak Levy, Amit Tirosh

2020Internal and Emergency Medicine288 citationsDOIOpen Access PDF

Topics & Concepts

MedicineTriageCoronavirus disease 2019 (COVID-19)Mechanical ventilationWhite blood cellEarly warning scoreEmergency medicineRetrospective cohort studySeverity of illnessOxygen saturationMachine learningOxygen therapyReceiver operating characteristicEmergency departmentIntensive care medicineInternal medicineDiseaseInfectious disease (medical specialty)ChemistryPsychiatryComputer scienceOxygenOrganic chemistryCOVID-19 Clinical Research StudiesCOVID-19 diagnosis using AISepsis Diagnosis and Treatment
Utilization of machine-learning models to accurately predict the risk for critical COVID-19 | Litcius