A Machine Learning Approach for Mortality Prediction in COVID-19 Pneumonia: Development and Evaluation of the Piacenza Score
Original Paper
[키워드] 30-Day mortality
95% CI
Accuracy
added
age
Algorithm
approach
artificial intelligence
AUC
characteristic
Characteristics
Classifier
Clinical data
Clinical outcome
Cohort
cohorts
collected
comparable
computation
Concentration
corpuscular hemoglobin
COVID-19
data-driven
demographics
demonstrated
develop
development
effective
evaluate
exhibited
external validation
feasible
feature
Gender
Health
Italy
machine
machine learning
modeling
Mortality
mortality risk
naïve
objective
outcomes
PaO
Patient
patient data
patients with COVID-19
Physicians
Pneumonia
predict
prediction
prognostic score
Randomly
Result
score
statistical
stroke
temperature
validation cohort
variable
was obtained
was used
website
[DOI] 10.2196/29058 PMC 바로가기 [Article Type] Original Paper
[DOI] 10.2196/29058 PMC 바로가기 [Article Type] Original Paper