The Development and Validation of Simplified Machine Learning Algorithms to Predict Prognosis of Hospitalized Patients With COVID-19: Multicenter, Retrospective Study
Original Paper
[키워드] 95% CI
acute respiratory distress
Admission
age
albumin
Algorithm
Analysis
approach
AUC
baseline
Blood
Blood urea nitrogen
Care
characteristic
Clinical characteristics
clinical feature
clinical utility
clinically
cognitive
cohort study
collected
Community
covariate
COVID-19
COVID-19 pandemic
database
deaths
demonstrated
develop
development
diagnosed
diastolic
discriminatory power
disease severity
disorder
EHR
evaluate
groups
Health
help
high accuracy
High-risk patients
Hospital admission
Hospitalized
ICU
ICU admissions
in-hospital mortality
intensive care
machine learning
machine learning algorithm
mechanical ventilator
mechanically ventilated
multicenter
objective
offer
pandemic
Patient
patients
patients with COVID-19
performed
physician
positive
predict
Predictive
predictive algorithm
predictor
produced
prognostic
prognostic model
provide
pulse
Randomly
resource
resources
Respiratory failure
Result
risk factor
risk score
SARS-CoV-2
second wave
sensitivity
specificity
stroke
study cohort
syndrome
temperature
tested
The United States
thresholds
utility
validation
with COVID-19
[DOI] 10.2196/31549 PMC 바로가기 [Article Type] Original Paper
[DOI] 10.2196/31549 PMC 바로가기 [Article Type] Original Paper