Other packages > Find by keyword >

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]
All associated links for this package
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 07 Oct. 2026.
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
Downloads during the last 30 days

Today's Hot Picks in Authors and Packages

blandr  
Bland-Altman Method Comparison
Carries out Bland Altman analyses (also known as a Tukey mean-difference plot) as described by JM B ...
Download / Learn more Package Citations See dependency  
ggTimeSeries  
Time Series Visualisations Using the Grammar of Graphics
Provides additional display mediums for time series visualisations. ...
Download / Learn more Package Citations See dependency  
plaqr  
Partially Linear Additive Quantile Regression
Estimation, prediction, thresholding, transformation, and plotting for partially linear additive qua ...
Download / Learn more Package Citations See dependency  
splm  
Econometric Models for Spatial Panel Data
ML and GM estimation and diagnostic testing of econometric models for spatial panel data. ...
Download / Learn more Package Citations See dependency  
skewlmm  
Scale Mixture of Skew-Normal Linear Mixed Models
It fits scale mixture of skew-normal linear mixed models using an expectation–maximization (EM) ty ...
Download / Learn more Package Citations See dependency  
PairedData  
Paired Data Analysis
Many datasets and a set of graphics (based on ggplot2), statistics, effect sizes and hypothesis test ...
Download / Learn more Package Citations See dependency  

28,905

R Packages

247,686

Dependencies

76,495

Author Associations

28,906

Publication Badges

© Copyright since 2022. All right reserved, rpkg.net.  Based in Cambridge, Massachusetts, USA