Predictive Modeling of Morbidity and Mortality in Patients Hospitalized With COVID-19 and its Clinical Implications: Algorithm Development and Interpretation
Original Paper
[키워드] 24 hour
24 hours
age
assist
AUC
Blood urea nitrogen
C-reactive protein
canonical markers
clinical
clinical activity
Clinical data
clinical decision
clinical marker
coronavirus
COVID-19
COVID-19 pandemic
Deceased
Decision making
development
Diabetic
Disease progression
disease severity
effort
elevated
Endpoint
Factor
feature
Final
Glucose
Gradient
Health care system
highest
hospital
Hospital stay
Hospitalization
ICU
identify
intensive care
lab value
lactate dehydrogenase
LDH
machine learning
marker
Model
modeling
morbidity
morbidity and mortality
Mortality
New York
New York City
objective
offered
outcome
outcomes
Patient
patient data
performance
peripheral oxygen saturation
positive
predict
prediction
Predictive
Predictive modeling
respiration rate
Result
Retrospective study
risk
SARS-CoV-2
severity
strain
Symptom
temperature
tested
treated
university
Ventilated
was obtained
with COVID-19
[DOI] 10.2196/29514 PMC 바로가기 [Article Type] Original Paper
[DOI] 10.2196/29514 PMC 바로가기 [Article Type] Original Paper