# -------------------------------------------- # CITATION file created with {cffr} R package # See also: https://docs.ropensci.org/cffr/ # -------------------------------------------- cff-version: 1.2.0 message: 'To cite package "ODT" in publications use:' type: software license: Artistic-2.0 title: 'ODT: Optimal Decision Trees Algorithm' version: 1.0.1 doi: 10.32614/CRAN.package.ODT abstract: Implements a tree-based method specifically designed for personalized medicine applications. By using genomic and mutational data, 'ODT' efficiently identifies optimal drug recommendations tailored to individual patient profiles. The 'ODT' algorithm constructs decision trees that bifurcate at each node, selecting the most relevant markers (discrete or continuous) and corresponding treatments, thus ensuring that recommendations are both personalized and statistically robust. This iterative approach enhances therapeutic decision-making by refining treatment suggestions until a predefined group size is achieved. Moreover, the simplicity and interpretability of the resulting trees make the method accessible to healthcare professionals. Includes functions for training the decision tree, making predictions on new samples or patients, and visualizing the resulting tree. For detailed insights into the methodology, please refer to Gimeno et al. (2023) . authors: - family-names: Eceiza given-names: Maddi - family-names: Ruiz given-names: Lucia - family-names: Rubio given-names: Angel email: arubio@unav.es - family-names: Sada Del Real given-names: Katyna email: ksada@unav.es repository: https://katynasada.r-universe.dev commit: 3ce5bf2b0d0327f305e26fedd0b84ac5a74ca1f1 contact: - family-names: Sada Del Real given-names: Katyna email: ksada@unav.es