evaluate_model_pro: Evaluate Prognostic Model Performance

In E2E: Ensemble Learning Framework for Diagnostic and Prognostic Modeling

Evaluate Prognostic Model Performance

Description

Comprehensive evaluation of survival models using:

1. Harrell's Concordance Index (C-index).

2. Time-dependent Area Under the ROC Curve (AUROC) at specified years.

3. Kaplan-Meier analysis comparing high vs. low risk groups (based on median split).

Usage

evaluate_model_pro(
  trained_model_obj = NULL,
  X_data = NULL,
  Y_surv_obj,
  sample_ids,
  years_to_evaluate = c(1, 3, 5),
  precomputed_score = NULL,
  meta_normalize_params = NULL
)

Arguments

trained_model_obj	A trained model object (optional if precomputed_score provided).
X_data	Features for prediction (optional if precomputed_score provided).
Y_surv_obj	True survival object.
sample_ids	Vector of IDs.
years_to_evaluate	Numeric vector of years for time-dependent AUC.
precomputed_score	Numeric vector of pre-calculated risk scores.
meta_normalize_params	Internal use.

Value

A list containing a dataframe of scores and a list of evaluation metrics.

E2E documentation built on March 22, 2026, 1:07 a.m.