An Interpretable Machine Learning-Based Automatic Clinical Score Generator


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Documentation for package ‘AutoScore’ version 0.2.0

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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)