Performance of MLP model
renal pathological impairment
RENAL FIBROSIS
In the training set, the MLP model achieved satisfactory diagnostic performance, with an AUC of 0.93 [95% confidence interval (CI) = 0.88 to 0.98], the sensitivity of 0.89 [95% CI = 0.79 to 0.95], specificity of 0.88 [95% CI = 0.76 to 0.95], and accuracy of 0.88 [95% CI = 0.81 to 0.93] (Receiver operating characteristic curves for differentiating moderate-severe renal fibrosis from mild one in the training (A) and test cohorts (B).Water-fall plots constructed by the multilayer perceptron model in the training (A) and test cohorts (B). The blue area below the threshold indicates individuals with moderate-severe impairment who were misclassified as having mild impairment. The pink part above the threshold indicates individuals with mild impairment who were misclassified as moderate-severe impairment.In the training and test cohorts, the Hosmer-Lemeshow test indicated a Calibration curves of the multilayer perceptron model prediction in the training (A) and test cohorts (B). Calibration curves depict the calibration of the established model in terms of the agreement between the predicted risks of moderate-severe renal pathological impairment and the observed outcomes of moderate-severe impairment. The y-axis shows actual moderate-severe impairment diagnoses, and the x-axis indicates the predicted moderate-severe impairment risk. The diagonal dotted line represents a perfect prediction by an ideal model. The solid line represents the performance of the model; a closer fit to the diagonal dotted line represents a more accurate prediction.