evaluate_predictions_pro: Evaluate Prognostic Predictions

In E2E: Ensemble Learning Framework for Diagnostic and Prognostic Modeling

Evaluate Prognostic Predictions

Description

A convenience wrapper to evaluate a data frame of prognostic predictions. This function is ideal for evaluating the output of apply_pro.

Usage

evaluate_predictions_pro(prediction_df, years_to_evaluate = c(1, 3, 5))

Arguments

prediction_df	A data frame containing predictions. Must include columns named ID, outcome, time, and score. This format matches the output of apply_pro.
years_to_evaluate	A numeric vector of specific years at which to calculate time-dependent AUROC.

Value

A list of evaluation metrics, including C-index, time-dependent AUROC, and Kaplan-Meier analysis results.

See Also

apply_pro, evaluate_model_pro

Examples

# Assume 'trained_model' and 'test_pro' data are available
if (requireNamespace("E2E", quietly = TRUE) &&
    "train_pro" %in% utils::data(package = "E2E")$results[,3] &&
    "test_pro" %in% utils::data(package = "E2E")$results[,3]) {

  data(train_pro, package = "E2E")
  data(test_pro, package = "E2E")
  initialize_modeling_system_pro()
  model_results <- models_pro(data = train_pro, model = "lasso_pro")

  # 1. Get predictions on new data
  predictions <- apply_pro(model_results$lasso_pro$model_object, test_pro)

  # 2. Evaluate these predictions using the simplified function
  evaluation_metrics <- evaluate_predictions_pro(predictions, years_to_evaluate = c(1, 3))
  print(evaluation_metrics)
}

E2E documentation built on Aug. 27, 2025, 1:09 a.m.