add_baseline |
Internal Function: Add baselines after second-step logistic regression (part of AutoScore Module 3) |

assign_score |
Internal Function: Automatically assign scores to each subjects given new data set and scoring table (Used for intermediate and final evaluation) |

AutoScore_fine_tuning |
AutoScore STEP(iv): Fine-tune the score by revising cut_vec with domain knowledge (AutoScore Module 5) |

AutoScore_parsimony |
AutoScore STEP(ii): Select the best model with parsimony plot (AutoScore Modules 2+3+4) |

AutoScore_rank |
AutoScore STEP(i): Rank variables with machine learning (AutoScore Module 1) |

AutoScore_testing |
AutoScore STEP(v): Evaluate the final score with ROC analysis (AutoScore Module 6) |

AutoScore_weighting |
AutoScore STEP(iii): Generate the initial score with the final list of variables (Re-run AutoScore Modules 2+3) |

change_reference |
Internal Function: Change Reference category after first-step logistic regression (part of AutoScore Module 3) |

check_data |
AutoScore function: Check whether the input dataset fulfill the requirement of the AutoScore |

compute_auc_val |
Internal function: Compute AUC based on validation set for plotting parsimony (AutoScore Module 4) |

compute_descriptive_table |
AutoScore function: Descriptive Analysis |

compute_multi_variable_table |
AutoScore function: Multivariate Analysis |

compute_score_table |
Internal function: Compute scoring table based on training dataset (AutoScore Module 3) |

compute_uni_variable_table |
AutoScore function: Univariable Analysis |

get_cut_vec |
Internal function: Calculate cut_vec from the training set (AutoScore Module 2) |

plot_roc_curve |
Internal Function: Plotting ROC curve |

print_roc_performance |
AutoScore function: Print receiver operating characteristic (ROC) performance |

print_scoring_table |
AutoScore Function: Print scoring tables for visualization |

sample_data |
20000 simulated ICU admission data, with the same distribution as the data in the MIMIC-III ICU database |

sample_data_small |
1000 simulated ICU admission data, with the same distribution as the data in the MIMIC-III ICU database |

split_data |
AutoScore function: Automatically splitting dataset to train, validation and test set |

transform_df_fixed |
Internal function: Categorizing continuous variables based on cut_vec (AutoScore Module 2) |