An Interpretable Machine Learning-Based Automatic Clinical Score Generator R package AutoScore version 1.1.0 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 details are described in our research paper<doi:10.2196/21798>. 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. Software Depends: R (>= 3.5.0) Imports: tableone, pROC, randomForest, ggplot2, knitr, Hmisc, car, dplyr, ordinal, survival, tidyr, plotly, magrittr, randomForestSRC, rlang, survAUC, survminer Suggests: rpart, rmarkdown Feng Xie <xief@u.duke.nus.edu> Comprehensive R Archive Network (CRAN) Feng Xie [aut, cre] (ORCID: <https://orcid.org/0000-0002-0215-667X>), Yilin Ning [aut] (ORCID: <https://orcid.org/0000-0002-6758-4472>), Han Yuan [aut] (ORCID: <https://orcid.org/0000-0002-2674-6068>), Mingxuan Liu [aut] (ORCID: <https://orcid.org/0000-0002-4274-9613>), Siqi Li [aut] (ORCID: <https://orcid.org/0000-0002-1660-105X>), Ehsan Saffari [aut] (ORCID: <https://orcid.org/0000-0002-6473-4375>), Bibhas Chakraborty [aut] (ORCID: <https://orcid.org/0000-0002-7366-0478>), Nan Liu [aut] (ORCID: <https://orcid.org/0000-0003-3610-4883>) GPL (>= 2) 2025-08-01 application/tgz https://CRAN.R-project.org/package=AutoScore doi:10.32614/CRAN.package.AutoScore