Custom model metrics.


balanced_accuracy(y_true, y_pred)

Balanced accuracy metric for multi-class labels.

classification_metrics(y_true, y_pred[, ...])

Compute several classification metrics. * AUROC * At Youden point: balanced accuracy, Youden's index, F1, PPV, NPV, sensitivity, specificity * Sensitivity at fixed specificity * Specificity at fixed sensitivity.

compute_youden_point(y_true, y_pred)

Compute Youden point (where the Youden index sensitivity + specificity - 1 is maximized)


Compute image metrics, including brightness, contrast, sharpness, and SNR

sensitivity_at_specificity(y_true, y_pred[, ...])

Compute sensitivity at fixed specificity.

single_sample_dice(y_true, y_pred[, threshold])

Compute Dice score

specificity_at_sensitivity(y_true, y_pred[, ...])

Compute specificity at fixed sensitivity.