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AutoScore
View on CRAN: Click
here
Download and install AutoScore package within the R console
Install from CRAN:
install.packages("AutoScore")
Install from Github:
library("remotes")
install_github("cran/AutoScore")
Install by package version:
library("remotes")
install_version("AutoScore", "1.0.0")
Attach the package and use:
library("AutoScore")
Maintained by
Feng Xie
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
https://nliulab.github.io/AutoScore/ . 10.32614/CRAN.package.AutoScore . https://github.com/nliulab/AutoScore/issues . https://github.com/nliulab/AutoScore . AutoScore citation info . AutoScore results . AutoScore.pdf . AutoScore_1.0.0.tar.gz . AutoScore_1.0.0.zip . AutoScore_1.0.0.zip . AutoScore_1.0.0.zip . AutoScore_1.0.0.tgz . AutoScore_1.0.0.tgz . AutoScore_1.0.0.tgz . AutoScore_1.0.0.tgz . AutoScore archive . https://CRAN.R-project.org/package=AutoScore .
First Published: 2021-06-16
Latest Update: 2022-10-15
Description:
A novel interpretable machine learning-based framework to automate the development of a clinical scoring model for predefined outcomes. Our novel framework consists of six modules: variable ranking with machine learning, variable transformation, score derivation, model selection, domain knowledge-based score fine-tuning, and performance evaluation.The The original AutoScore structure is described in the research paper. A full tutorial can be found here. Users or clinicians could seamlessly generate parsimonious sparse-score risk models (i.e., risk scores), which can be easily implemented and validated in clinical practice. We hope to see its application in various medical case studies.
How to cite:
Feng Xie (2021). AutoScore: An Interpretable Machine Learning-Based Automatic Clinical Score Generator. R package version 1.0.0, https://cran.r-project.org/web/packages/AutoScore. Accessed 05 May. 2025.
Other packages that cited AutoScore R package
View AutoScore citation profile
Other R packages that AutoScore depends,
imports, suggests or enhances
Complete documentation for AutoScore
Functions, R codes and Examples using
the AutoScore R package
Some associated functions: AutoScore_fine_tuning . AutoScore_fine_tuning_Ordinal . AutoScore_fine_tuning_Survival . AutoScore_parsimony . AutoScore_parsimony_Ordinal . AutoScore_parsimony_Survival . AutoScore_rank . AutoScore_rank_Ordinal . AutoScore_rank_Survival . AutoScore_testing . AutoScore_testing_Ordinal . AutoScore_testing_Survival . AutoScore_weighting . AutoScore_weighting_Ordinal . AutoScore_weighting_Survival . add_baseline . assign_score . change_reference . check_data . check_data_ordinal . check_data_survival . check_link . check_predictor . compute_auc_val . compute_auc_val_ord . compute_auc_val_survival . compute_descriptive_table . compute_final_score_ord . compute_mauc_ord . compute_multi_variable_table . compute_multi_variable_table_ordinal . compute_multi_variable_table_survival . compute_prob_observed . compute_prob_predicted . compute_score_table . compute_score_table_ord . compute_score_table_survival . compute_uni_variable_table . compute_uni_variable_table_ordinal . compute_uni_variable_table_survival . conversion_table . conversion_table_ordinal . conversion_table_survival . estimate_p_mat . eva_performance_iauc . evaluate_model_ord . extract_or_ci_ord . find_one_inds . find_possible_scores . get_cut_vec . group_score . induce_informative_missing . induce_median_missing . inv_cloglog . inv_logit . inv_probit . make_design_mat . plot_auc . plot_importance . plot_predicted_risk . plot_roc_curve . plot_survival_km . print_performance_ci_survival . print_performance_ordinal . print_performance_survival . print_roc_performance . print_scoring_table . sample_data . sample_data_ordinal . sample_data_ordinal_small . sample_data_small . sample_data_survival . sample_data_survival_small . sample_data_with_missing . split_data . transform_df_fixed .
Some associated R codes: AutoScore.R . AutoScore_Ordinal.R . AutoScore_Survival.R . common.R . Full AutoScore package functions and examples
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