Fig. 5
From: A predictive model for post-COVID-19 pulmonary parenchymal abnormalities based on dual-center data
Calibration curve of the residual probability of lung parenchymal abnormality nomogram prediction. (A) Calibration curve from the training set. (B) Calibration curve from the validation set. The Ideal line represented the ideal state, the Apparent line provided the model’s performance on the training set, and the Bias-corrected line was a better estimate of the model’s performance on validation set by correcting the Apparent line. The closer the Bias-corrected curve was to the Ideal straight line, the better the results.
