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ODT  

Optimal Decision Trees Algorithm
View on CRAN: Click here


Download and install ODT package within the R console
Install from CRAN:
install.packages("ODT")

Install from Github:
library("remotes")
install_github("cran/ODT")

Install by package version:
library("remotes")
install_version("ODT", "1.0.0")



Attach the package and use:
library("ODT")
Maintained by
Katyna Sada Del Real
[Scholar Profile | Author Map]
First Published: 2024-10-18
Latest Update: 2024-10-18
Description:
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) <doi:10.1093/bib/bbad200>.
How to cite:
Katyna Sada Del Real (2024). ODT: Optimal Decision Trees Algorithm. R package version 1.0.0, https://cran.r-project.org/web/packages/ODT. Accessed 29 Mar. 2025.
Previous versions and publish date:
No previous versions
Other packages that cited ODT R package
View ODT citation profile
Other R packages that ODT depends, imports, suggests or enhances
Complete documentation for ODT
Functions, R codes and Examples using the ODT R package
Full ODT package functions and examples
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