Table 4 Prediction performance using all clinical features.

From: Budget constrained machine learning for early prediction of adverse outcomes for COVID-19 patients

Model

Outcome

AP mean (std)

AUC mean (std)

XGBoost

Composite ventilation

0.379 (0.038)

0.723 (0.038)

Gaussian process

Composite ventilation

0.357 (0.037)

0.713 (0.023)

Logistic regression

Composite ventilation

0.361 (0.035)

0.717 (0.013)

XGBoost

Mortality

0.354 (0.065)

0.802 (0.029)

Gaussian process

Mortality

0.338 (0.055)

0.819 (0.012)

Logistic regression

Mortality

0.328 (0.067)

0.805 (0.029)

  1. Adverse outcome prediction performance at the point of entry for the various ML models in terms of average precision (AP) and area under receiver operating curve (AUC).
Back to article page